---
_id: '543'
abstract:
- lang: eng
text: A central goal in theoretical neuroscience is to predict the response properties
of sensory neurons from first principles. To this end, “efficient coding” posits
that sensory neurons encode maximal information about their inputs given internal
constraints. There exist, however, many variants of efficient coding (e.g., redundancy
reduction, different formulations of predictive coding, robust coding, sparse
coding, etc.), differing in their regimes of applicability, in the relevance of
signals to be encoded, and in the choice of constraints. It is unclear how these
types of efficient coding relate or what is expected when different coding objectives
are combined. Here we present a unified framework that encompasses previously
proposed efficient coding models and extends to unique regimes. We show that optimizing
neural responses to encode predictive information can lead them to either correlate
or decorrelate their inputs, depending on the stimulus statistics; in contrast,
at low noise, efficiently encoding the past always predicts decorrelation. Later,
we investigate coding of naturalistic movies and show that qualitatively different
types of visual motion tuning and levels of response sparsity are predicted, depending
on whether the objective is to recover the past or predict the future. Our approach
promises a way to explain the observed diversity of sensory neural responses,
as due to multiple functional goals and constraints fulfilled by different cell
types and/or circuits.
article_processing_charge: No
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Chalk MJ, Marre O, Tkačik G. Toward a unified theory of efficient, predictive,
and sparse coding. PNAS. 2018;115(1):186-191. doi:10.1073/pnas.1711114115
apa: Chalk, M. J., Marre, O., & Tkačik, G. (2018). Toward a unified theory of
efficient, predictive, and sparse coding. PNAS. National Academy of Sciences.
https://doi.org/10.1073/pnas.1711114115
chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Toward a Unified Theory
of Efficient, Predictive, and Sparse Coding.” PNAS. National Academy of
Sciences, 2018. https://doi.org/10.1073/pnas.1711114115.
ieee: M. J. Chalk, O. Marre, and G. Tkačik, “Toward a unified theory of efficient,
predictive, and sparse coding,” PNAS, vol. 115, no. 1. National Academy
of Sciences, pp. 186–191, 2018.
ista: Chalk MJ, Marre O, Tkačik G. 2018. Toward a unified theory of efficient, predictive,
and sparse coding. PNAS. 115(1), 186–191.
mla: Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive,
and Sparse Coding.” PNAS, vol. 115, no. 1, National Academy of Sciences,
2018, pp. 186–91, doi:10.1073/pnas.1711114115.
short: M.J. Chalk, O. Marre, G. Tkačik, PNAS 115 (2018) 186–191.
date_created: 2018-12-11T11:47:04Z
date_published: 2018-01-02T00:00:00Z
date_updated: 2023-09-19T10:16:35Z
day: '02'
department:
- _id: GaTk
doi: 10.1073/pnas.1711114115
external_id:
isi:
- '000419128700049'
intvolume: ' 115'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/152660 '
month: '01'
oa: 1
oa_version: Submitted Version
page: 186 - 191
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7273'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Toward a unified theory of efficient, predictive, and sparse coding
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '607'
abstract:
- lang: eng
text: We study the Fokker-Planck equation derived in the large system limit of the
Markovian process describing the dynamics of quantitative traits. The Fokker-Planck
equation is posed on a bounded domain and its transport and diffusion coefficients
vanish on the domain's boundary. We first argue that, despite this degeneracy,
the standard no-flux boundary condition is valid. We derive the weak formulation
of the problem and prove the existence and uniqueness of its solutions by constructing
the corresponding contraction semigroup on a suitable function space. Then, we
prove that for the parameter regime with high enough mutation rate the problem
exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next,
we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt)
method for approximation of observables (moments) of the Fokker-Planck solution,
which can be interpreted as a nonlinear Galerkin approximation. The limited applicability
of the DynMaxEnt method inspires us to introduce its modified version that is
valid for the whole range of admissible parameters. Finally, we present several
numerical experiments to demonstrate the performance of both the original and
modified DynMaxEnt methods. We observe that in the parameter regimes where both
methods are valid, the modified one exhibits slightly better approximation properties
compared to the original one.
acknowledgement: "JH and PM are funded by KAUST baseline funds and grant no. 1000000193
.\r\nWe thank Nicholas Barton (IST Austria) for his useful comments and suggestions.
\r\n\r\n"
article_processing_charge: No
author:
- first_name: Katarina
full_name: Bodova, Katarina
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bodova
orcid: 0000-0002-7214-0171
- first_name: Jan
full_name: Haskovec, Jan
last_name: Haskovec
- first_name: Peter
full_name: Markowich, Peter
last_name: Markowich
citation:
ama: 'Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation
for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena.
2018;376-377:108-120. doi:10.1016/j.physd.2017.10.015'
apa: 'Bodova, K., Haskovec, J., & Markowich, P. (2018). Well posedness and maximum
entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear
Phenomena. Elsevier. https://doi.org/10.1016/j.physd.2017.10.015'
chicago: 'Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and
Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica
D: Nonlinear Phenomena. Elsevier, 2018. https://doi.org/10.1016/j.physd.2017.10.015.'
ieee: 'K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy
approximation for the dynamics of quantitative traits,” Physica D: Nonlinear
Phenomena, vol. 376–377. Elsevier, pp. 108–120, 2018.'
ista: 'Bodova K, Haskovec J, Markowich P. 2018. Well posedness and maximum entropy
approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena.
376–377, 108–120.'
mla: 'Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation
for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena,
vol. 376–377, Elsevier, 2018, pp. 108–20, doi:10.1016/j.physd.2017.10.015.'
short: 'K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377
(2018) 108–120.'
date_created: 2018-12-11T11:47:28Z
date_published: 2018-08-01T00:00:00Z
date_updated: 2023-09-19T10:38:34Z
day: '01'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1016/j.physd.2017.10.015
external_id:
arxiv:
- '1704.08757'
isi:
- '000437962900012'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1704.08757
month: '08'
oa: 1
oa_version: Submitted Version
page: 108-120
publication: 'Physica D: Nonlinear Phenomena'
publication_status: published
publisher: Elsevier
publist_id: '7198'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Well posedness and maximum entropy approximation for the dynamics of quantitative
traits
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 376-377
year: '2018'
...
---
_id: '19'
abstract:
- lang: eng
text: Bacteria regulate genes to survive antibiotic stress, but regulation can be
far from perfect. When regulation is not optimal, mutations that change gene expression
can contribute to antibiotic resistance. It is not systematically understood to
what extent natural gene regulation is or is not optimal for distinct antibiotics,
and how changes in expression of specific genes quantitatively affect antibiotic
resistance. Here we discover a simple quantitative relation between fitness, gene
expression, and antibiotic potency, which rationalizes our observation that a
multitude of genes and even innate antibiotic defense mechanisms have expression
that is critically nonoptimal under antibiotic treatment. First, we developed
a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression
and knockout libraries, finding that resistance to a range of 31 antibiotics could
result from changing expression of a large and functionally diverse set of genes,
in a primarily but not exclusively drug-specific manner. Second, by synthetically
controlling the expression of single-drug and multidrug resistance genes, we observed
that their fitness-expression functions changed dramatically under antibiotic
treatment in accordance with a log-sensitivity relation. Thus, because many genes
are nonoptimally expressed under antibiotic treatment, many regulatory mutations
can contribute to resistance by altering expression and by activating latent defenses.
article_processing_charge: No
article_type: original
author:
- first_name: Adam
full_name: Palmer, Adam
last_name: Palmer
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential
for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684.
doi:10.1093/molbev/msy163
apa: Palmer, A., Chait, R. P., & Kishony, R. (2018). Nonoptimal gene expression
creates latent potential for antibiotic resistance. Molecular Biology and Evolution.
Oxford University Press. https://doi.org/10.1093/molbev/msy163
chicago: Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression
Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and
Evolution. Oxford University Press, 2018. https://doi.org/10.1093/molbev/msy163.
ieee: A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates
latent potential for antibiotic resistance,” Molecular Biology and Evolution,
vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018.
ista: Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent
potential for antibiotic resistance. Molecular Biology and Evolution. 35(11),
2669–2684.
mla: Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for
Antibiotic Resistance.” Molecular Biology and Evolution, vol. 35, no. 11,
Oxford University Press, 2018, pp. 2669–84, doi:10.1093/molbev/msy163.
short: A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018)
2669–2684.
date_created: 2018-12-11T11:44:11Z
date_published: 2018-08-28T00:00:00Z
date_updated: 2023-10-17T11:51:06Z
day: '28'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1093/molbev/msy163
external_id:
isi:
- '000452567200006'
pmid:
- '30169679'
intvolume: ' 35'
isi: 1
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pubmed/30169679
month: '08'
oa: 1
oa_version: Submitted Version
page: 2669 - 2684
pmid: 1
publication: Molecular Biology and Evolution
publication_identifier:
issn:
- 0737-4038
publication_status: published
publisher: Oxford University Press
publist_id: '8036'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Nonoptimal gene expression creates latent potential for antibiotic resistance
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2018'
...
---
_id: '292'
abstract:
- lang: eng
text: 'Retina is a paradigmatic system for studying sensory encoding: the transformation
of light into spiking activity of ganglion cells. The inverse problem, where stimulus
is reconstructed from spikes, has received less attention, especially for complex
stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred
neurons from a dense patch in a rat retina and decoded movies of multiple small
randomly-moving discs. We constructed nonlinear (kernelized and neural network)
decoders that improved significantly over linear results. An important contribution
to this was the ability of nonlinear decoders to reliably separate between neural
responses driven by locally fluctuating light signals, and responses at locally
constant light driven by spontaneous-like activity. This improvement crucially
depended on the precise, non-Poisson temporal structure of individual spike trains,
which originated in the spike-history dependence of neural responses. We propose
a general principle by which downstream circuitry could discriminate between spontaneous
and stimulus-driven activity based solely on higher-order statistical structure
in the incoming spike trains.'
article_number: e1006057
article_processing_charge: Yes
article_type: original
author:
- first_name: Vicent
full_name: Botella Soler, Vicent
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Georg S
full_name: Martius, Georg S
last_name: Martius
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. Nonlinear decoding
of a complex movie from the mammalian retina. PLoS Computational Biology.
2018;14(5). doi:10.1371/journal.pcbi.1006057
apa: Botella Soler, V., Deny, S., Martius, G. S., Marre, O., & Tkačik, G. (2018).
Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1006057
chicago: Botella Soler, Vicente, Stephane Deny, Georg S Martius, Olivier Marre,
and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.”
PLoS Computational Biology. Public Library of Science, 2018. https://doi.org/10.1371/journal.pcbi.1006057.
ieee: V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkačik, “Nonlinear
decoding of a complex movie from the mammalian retina,” PLoS Computational
Biology, vol. 14, no. 5. Public Library of Science, 2018.
ista: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. 2018. Nonlinear decoding
of a complex movie from the mammalian retina. PLoS Computational Biology. 14(5),
e1006057.
mla: Botella Soler, Vicente, et al. “Nonlinear Decoding of a Complex Movie from
the Mammalian Retina.” PLoS Computational Biology, vol. 14, no. 5, e1006057,
Public Library of Science, 2018, doi:10.1371/journal.pcbi.1006057.
short: V. Botella Soler, S. Deny, G.S. Martius, O. Marre, G. Tkačik, PLoS Computational
Biology 14 (2018).
date_created: 2018-12-11T11:45:39Z
date_published: 2018-05-10T00:00:00Z
date_updated: 2024-02-21T13:45:25Z
day: '10'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1006057
ec_funded: 1
external_id:
isi:
- '000434012100002'
file:
- access_level: open_access
checksum: 3026f94d235219e15514505fdbadf34e
content_type: application/pdf
creator: dernst
date_created: 2019-02-13T11:07:15Z
date_updated: 2020-07-14T12:45:53Z
file_id: '5974'
file_name: 2018_Plos_Botella_Soler.pdf
file_size: 3460786
relation: main_file
file_date_updated: 2020-07-14T12:45:53Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
issue: '5'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '05'
oa: 1
oa_version: Published Version
project:
- _id: 25CBA828-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '720270'
name: Human Brain Project Specific Grant Agreement 1 (HBP SGA 1)
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/video-of-moving-discs-reconstructed-from-rat-retinal-neuron-signals/
record:
- id: '5584'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Nonlinear decoding of a complex movie from the mammalian retina
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 14
year: '2018'
...
---
_id: '161'
abstract:
- lang: eng
text: 'Which properties of metabolic networks can be derived solely from stoichiometry?
Predictive results have been obtained by flux balance analysis (FBA), by postulating
that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization
of FBA to single-cell level using maximum entropy modeling, which we extend and
test experimentally. Specifically, we define for Escherichia coli metabolism a
flux distribution that yields the experimental growth rate: the model, containing
FBA as a limit, provides a better match to measured fluxes and it makes a wide
range of predictions: on flux variability, regulation, and correlations; on the
relative importance of stoichiometry vs. optimization; on scaling relations for
growth rate distributions. We validate the latter here with single-cell data at
different sub-inhibitory antibiotic concentrations. The model quantifies growth
optimization as emerging from the interplay of competitive dynamics in the population
and regulation of metabolism at the level of single cells.'
article_number: '2988'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Andersson Anna
full_name: Mc, Andersson Anna
last_name: Mc
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications.
2018;9(1). doi:10.1038/s41467-018-05417-9
apa: De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018).
Statistical mechanics for metabolic networks during steady state growth. Nature
Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9
chicago: De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet,
and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady
State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9.
ieee: D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical
mechanics for metabolic networks during steady state growth,” Nature Communications,
vol. 9, no. 1. Springer Nature, 2018.
ista: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications. 9(1),
2988.
mla: De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during
Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer
Nature, 2018, doi:10.1038/s41467-018-05417-9.
short: D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications
9 (2018).
date_created: 2018-12-11T11:44:57Z
date_published: 2018-07-30T00:00:00Z
date_updated: 2024-02-21T13:45:39Z
day: '30'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.1038/s41467-018-05417-9
ec_funded: 1
external_id:
isi:
- '000440149300021'
file:
- access_level: open_access
checksum: 3ba7ab27b27723c7dcf633e8fc1f8f18
content_type: application/pdf
creator: dernst
date_created: 2018-12-17T16:44:28Z
date_updated: 2020-07-14T12:45:06Z
file_id: '5728'
file_name: 2018_NatureComm_DeMartino.pdf
file_size: 1043205
relation: main_file
file_date_updated: 2020-07-14T12:45:06Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Nature Communications
publication_status: published
publisher: Springer Nature
publist_id: '7760'
quality_controlled: '1'
related_material:
record:
- id: '5587'
relation: popular_science
status: public
scopus_import: '1'
status: public
title: Statistical mechanics for metabolic networks during steady state growth
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 9
year: '2018'
...
---
_id: '67'
abstract:
- lang: eng
text: 'Gene regulatory networks evolve through rewiring of individual components—that
is, through changes in regulatory connections. However, the mechanistic basis
of regulatory rewiring is poorly understood. Using a canonical gene regulatory
system, we quantify the properties of transcription factors that determine the
evolutionary potential for rewiring of regulatory connections: robustness, tunability
and evolvability. In vivo repression measurements of two repressors at mutated
operator sites reveal their contrasting evolutionary potential: while robustness
and evolvability were positively correlated, both were in trade-off with tunability.
Epistatic interactions between adjacent operators alleviated this trade-off. A
thermodynamic model explains how the differences in robustness, tunability and
evolvability arise from biophysical characteristics of repressor–DNA binding.
The model also uncovers that the energy matrix, which describes how mutations
affect repressor–DNA binding, encodes crucial information about the evolutionary
potential of a repressor. The biophysical determinants of evolutionary potential
for regulatory rewiring constitute a mechanistic framework for understanding network
evolution.'
article_processing_charge: No
article_type: original
author:
- first_name: Claudia
full_name: Igler, Claudia
id: 46613666-F248-11E8-B48F-1D18A9856A87
last_name: Igler
- first_name: Mato
full_name: Lagator, Mato
id: 345D25EC-F248-11E8-B48F-1D18A9856A87
last_name: Lagator
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential
of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution.
2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y
apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018).
Evolutionary potential of transcription factors for gene regulatory rewiring.
Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y
chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin
C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.”
Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y.
ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary
potential of transcription factors for gene regulatory rewiring,” Nature Ecology
and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018.
ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential
of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution.
2(10), 1633–1643.
mla: Igler, Claudia, et al. “Evolutionary Potential of Transcription Factors for
Gene Regulatory Rewiring.” Nature Ecology and Evolution, vol. 2, no. 10,
Nature Publishing Group, 2018, pp. 1633–43, doi:10.1038/s41559-018-0651-y.
short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology
and Evolution 2 (2018) 1633–1643.
date_created: 2018-12-11T11:44:27Z
date_published: 2018-09-10T00:00:00Z
date_updated: 2024-03-28T23:30:49Z
day: '10'
ddc:
- '570'
department:
- _id: CaGu
- _id: GaTk
- _id: JoBo
doi: 10.1038/s41559-018-0651-y
ec_funded: 1
external_id:
isi:
- '000447947600021'
file:
- access_level: open_access
checksum: 383a2e2c944a856e2e821ec8e7bf71b6
content_type: application/pdf
creator: dernst
date_created: 2020-05-14T11:28:52Z
date_updated: 2020-07-14T12:47:37Z
file_id: '7830'
file_name: 2018_NatureEcology_Igler.pdf
file_size: 1135973
relation: main_file
file_date_updated: 2020-07-14T12:47:37Z
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intvolume: ' 2'
isi: 1
issue: '10'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Submitted Version
page: 1633 - 1643
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2578D616-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '648440'
name: Selective Barriers to Horizontal Gene Transfer
- _id: 251EE76E-B435-11E9-9278-68D0E5697425
grant_number: '24573'
name: Design principles underlying genetic switch architecture (DOC Fellowship)
publication: Nature Ecology and Evolution
publication_status: published
publisher: Nature Publishing Group
publist_id: '7987'
quality_controlled: '1'
related_material:
record:
- id: '5585'
relation: popular_science
status: public
- id: '6371'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Evolutionary potential of transcription factors for gene regulatory rewiring
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2
year: '2018'
...
---
_id: '613'
abstract:
- lang: eng
text: 'Bacteria in groups vary individually, and interact with other bacteria and
the environment to produce population-level patterns of gene expression. Investigating
such behavior in detail requires measuring and controlling populations at the
single-cell level alongside precisely specified interactions and environmental
characteristics. Here we present an automated, programmable platform that combines
image-based gene expression and growth measurements with on-line optogenetic expression
control for hundreds of individual Escherichia coli cells over days, in a dynamically
adjustable environment. This integrated platform broadly enables experiments that
bridge individual and population behaviors. We demonstrate: (i) population structuring
by independent closed-loop control of gene expression in many individual cells,
(ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid
bio-digital circuits in single cells, and freely specifiable digital communication
between individual bacteria. These examples showcase the potential for real-time
integration of theoretical models with measurement and control of many individual
cells to investigate and engineer microbial population behavior.'
acknowledgement: We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis,
M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and
Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich,
T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild,
B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin
for technical assistance. The research leading to these results has received funding
from the People Programme (Marie Curie Actions) of the European Union’s Seventh
Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to
R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST
Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence
Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025
(COGEX) and ANR-10-BINF-06-01 (ICEBERG).
article_number: '1535'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population
behavior through computer interfaced control of individual cells. Nature Communications.
2017;8(1). doi:10.1038/s41467-017-01683-1
apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017).
Shaping bacterial population behavior through computer interfaced control of individual
cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1
chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin
C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control
of Individual Cells.” Nature Communications. Nature Publishing Group, 2017.
https://doi.org/10.1038/s41467-017-01683-1.
ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping
bacterial population behavior through computer interfaced control of individual
cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group,
2017.
ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial
population behavior through computer interfaced control of individual cells. Nature
Communications. 8(1), 1535.
mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer
Interfaced Control of Individual Cells.” Nature Communications, vol. 8,
no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1.
short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications
8 (2017).
date_created: 2018-12-11T11:47:30Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2021-01-12T08:06:15Z
day: '01'
ddc:
- '576'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41467-017-01683-1
ec_funded: 1
file:
- access_level: open_access
checksum: 44bb5d0229926c23a9955d9fe0f9723f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:05Z
date_updated: 2020-07-14T12:47:20Z
file_id: '5190'
file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf
file_size: 1951699
relation: main_file
file_date_updated: 2020-07-14T12:47:20Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '7191'
pubrep_id: '911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Shaping bacterial population behavior through computer interfaced control of
individual cells
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2017'
...
---
_id: '652'
abstract:
- lang: eng
text: 'We present an approach that enables robots to self-organize their sensorimotor
behavior from scratch without providing specific information about neither the
robot nor its environment. This is achieved by a simple neural control law that
increases the consistency between external sensor dynamics and internal neural
dynamics of the utterly simple controller. In this way, the embodiment and the
agent-environment coupling are the only source of individual development. We show
how an anthropomorphic tendon driven arm-shoulder system develops different behaviors
depending on that coupling. For instance: Given a bottle half-filled with water,
the arm starts to shake it, driven by the physical response of the water. When
attaching a brush, the arm can be manipulated into wiping a table, and when connected
to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said
to discover the affordances of the world. When allowing two (simulated) humanoid
robots to interact physically, they engage into a joint behavior development leading
to, for instance, spontaneous cooperation. More social effects are observed if
the robots can visually perceive each other. Although, as an observer, it is tempting
to attribute an apparent intentionality, there is nothing of the kind put in.
As a conclusion, we argue that emergent behavior may be much less rooted in explicit
intentions, internal motivations, or specific reward systems than is commonly
believed.'
article_number: '7846789'
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: 'Der R, Martius GS. Dynamical self consistency leads to behavioral development
and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789'
apa: 'Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to
behavioral development and emergent social interactions in robots. Presented at
the ICDL EpiRob: International Conference on Development and Learning and Epigenetic
Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789'
chicago: Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral
Development and Emergent Social Interactions in Robots.” IEEE, 2017. https://doi.org/10.1109/DEVLRN.2016.7846789.
ieee: 'R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral
development and emergent social interactions in robots,” presented at the ICDL
EpiRob: International Conference on Development and Learning and Epigenetic Robotics
, Cergy-Pontoise, France, 2017.'
ista: 'Der R, Martius GS. 2017. Dynamical self consistency leads to behavioral development
and emergent social interactions in robots. ICDL EpiRob: International Conference
on Development and Learning and Epigenetic Robotics , 7846789.'
mla: Der, Ralf, and Georg S. Martius. Dynamical Self Consistency Leads to Behavioral
Development and Emergent Social Interactions in Robots. 7846789, IEEE, 2017,
doi:10.1109/DEVLRN.2016.7846789.
short: R. Der, G.S. Martius, in:, IEEE, 2017.
conference:
end_date: 2016-09-22
location: Cergy-Pontoise, France
name: 'ICDL EpiRob: International Conference on Development and Learning and Epigenetic
Robotics '
start_date: 2016-09-19
date_created: 2018-12-11T11:47:43Z
date_published: 2017-02-07T00:00:00Z
date_updated: 2021-01-12T08:07:51Z
day: '07'
department:
- _id: ChLa
- _id: GaTk
doi: 10.1109/DEVLRN.2016.7846789
language:
- iso: eng
month: '02'
oa_version: None
publication_identifier:
isbn:
- 978-150905069-7
publication_status: published
publisher: IEEE
publist_id: '7100'
quality_controlled: '1'
scopus_import: 1
status: public
title: Dynamical self consistency leads to behavioral development and emergent social
interactions in robots
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '658'
abstract:
- lang: eng
text: 'With the accelerated development of robot technologies, control becomes one
of the central themes of research. In traditional approaches, the controller,
by its internal functionality, finds appropriate actions on the basis of specific
objectives for the task at hand. While very successful in many applications, self-organized
control schemes seem to be favored in large complex systems with unknown dynamics
or which are difficult to model. Reasons are the expected scalability, robustness,
and resilience of self-organizing systems. The paper presents a self-learning
neurocontroller based on extrinsic differential plasticity introduced recently,
applying it to an anthropomorphic musculoskeletal robot arm with attached objects
of unknown physical dynamics. The central finding of the paper is the following
effect: by the mere feedback through the internal dynamics of the object, the
robot is learning to relate each of the objects with a very specific sensorimotor
pattern. Specifically, an attached pendulum pilots the arm into a circular motion,
a half-filled bottle produces axis oriented shaking behavior, a wheel is getting
rotated, and wiping patterns emerge automatically in a table-plus-brush setting.
By these object-specific dynamical patterns, the robot may be said to recognize
the object''s identity, or in other words, it discovers dynamical affordances
of objects. Furthermore, when including hand coordinates obtained from a camera,
a dedicated hand-eye coordination self-organizes spontaneously. These phenomena
are discussed from a specific dynamical system perspective. Central is the dedicated
working regime at the border to instability with its potentially infinite reservoir
of (limit cycle) attractors "waiting" to be excited. Besides converging
toward one of these attractors, variate behavior is also arising from a self-induced
attractor morphing driven by the learning rule. We claim that experimental investigations
with this anthropomorphic, self-learning robot not only generate interesting and
potentially useful behaviors, but may also help to better understand what subjective
human muscle feelings are, how they can be rooted in sensorimotor patterns, and
how these concepts may feed back on robotics.'
article_number: '00008'
article_processing_charge: Yes
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots.
Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008
apa: Der, R., & Martius, G. S. (2017). Self organized behavior generation for
musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research
Foundation. https://doi.org/10.3389/fnbot.2017.00008
chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for
Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research
Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008.
ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal
robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research
Foundation, 2017.
ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal
robots. Frontiers in Neurorobotics. 11(MAR), 00008.
mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal
Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers
Research Foundation, 2017, doi:10.3389/fnbot.2017.00008.
short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2021-01-12T08:08:04Z
day: '16'
ddc:
- '006'
department:
- _id: ChLa
- _id: GaTk
doi: 10.3389/fnbot.2017.00008
ec_funded: 1
file:
- access_level: open_access
checksum: b1bc43f96d1df3313c03032c2a46388d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:49Z
date_updated: 2020-07-14T12:47:33Z
file_id: '5371'
file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf
file_size: 8439566
relation: main_file
file_date_updated: 2020-07-14T12:47:33Z
has_accepted_license: '1'
intvolume: ' 11'
issue: MAR
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Frontiers in Neurorobotics
publication_identifier:
issn:
- '16625218'
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '7078'
pubrep_id: '903'
quality_controlled: '1'
scopus_import: 1
status: public
title: Self organized behavior generation for musculoskeletal robots
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2017'
...
---
_id: '720'
abstract:
- lang: eng
text: 'Advances in multi-unit recordings pave the way for statistical modeling of
activity patterns in large neural populations. Recent studies have shown that
the summed activity of all neurons strongly shapes the population response. A
separate recent finding has been that neural populations also exhibit criticality,
an anomalously large dynamic range for the probabilities of different population
activity patterns. Motivated by these two observations, we introduce a class of
probabilistic models which takes into account the prior knowledge that the neural
population could be globally coupled and close to critical. These models consist
of an energy function which parametrizes interactions between small groups of
neurons, and an arbitrary positive, strictly increasing, and twice differentiable
function which maps the energy of a population pattern to its probability. We
show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an
accurate description of the activity of retinal ganglion cells which outperforms
previous models based on the summed activity of neurons; 2) prior knowledge that
the population is critical translates to prior expectations about the shape of
the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous
latent variable globally coupling the system whose distribution we can infer from
data. Our method is independent of the underlying system’s state space; hence,
it can be applied to other systems such as natural scenes or amino acid sequences
of proteins which are also known to exhibit criticality.'
article_number: e1005763
article_processing_charge: Yes
author:
- first_name: Jan
full_name: Humplik, Jan
id: 2E9627A8-F248-11E8-B48F-1D18A9856A87
last_name: Humplik
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Humplik J, Tkačik G. Probabilistic models for neural populations that naturally
capture global coupling and criticality. PLoS Computational Biology. 2017;13(9).
doi:10.1371/journal.pcbi.1005763
apa: Humplik, J., & Tkačik, G. (2017). Probabilistic models for neural populations
that naturally capture global coupling and criticality. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005763
chicago: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations
That Naturally Capture Global Coupling and Criticality.” PLoS Computational
Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005763.
ieee: J. Humplik and G. Tkačik, “Probabilistic models for neural populations that
naturally capture global coupling and criticality,” PLoS Computational Biology,
vol. 13, no. 9. Public Library of Science, 2017.
ista: Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that
naturally capture global coupling and criticality. PLoS Computational Biology.
13(9), e1005763.
mla: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations
That Naturally Capture Global Coupling and Criticality.” PLoS Computational
Biology, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005763.
short: J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017).
date_created: 2018-12-11T11:48:08Z
date_published: 2017-09-19T00:00:00Z
date_updated: 2021-01-12T08:12:21Z
day: '19'
ddc:
- '530'
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005763
file:
- access_level: open_access
checksum: 81107096c19771c36ddbe6f0282a3acb
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:30Z
date_updated: 2020-07-14T12:47:53Z
file_id: '5352'
file_name: IST-2017-884-v1+1_journal.pcbi.1005763.pdf
file_size: 14167050
relation: main_file
file_date_updated: 2020-07-14T12:47:53Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '6960'
pubrep_id: '884'
quality_controlled: '1'
scopus_import: 1
status: public
title: Probabilistic models for neural populations that naturally capture global coupling
and criticality
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2017'
...
---
_id: '725'
abstract:
- lang: eng
text: Individual computations and social interactions underlying collective behavior
in groups of animals are of great ethological, behavioral, and theoretical interest.
While complex individual behaviors have successfully been parsed into small dictionaries
of stereotyped behavioral modes, studies of collective behavior largely ignored
these findings; instead, their focus was on inferring single, mode-independent
social interaction rules that reproduced macroscopic and often qualitative features
of group behavior. Here, we bring these two approaches together to predict individual
swimming patterns of adult zebrafish in a group. We show that fish alternate between
an “active” mode, in which they are sensitive to the swimming patterns of conspecifics,
and a “passive” mode, where they ignore them. Using a model that accounts for
these two modes explicitly, we predict behaviors of individual fish with high
accuracy, outperforming previous approaches that assumed a single continuous computation
by individuals and simple metric or topological weighing of neighbors’ behavior.
At the group level, switching between active and passive modes is uncorrelated
among fish, but correlated directional swimming behavior still emerges. Our quantitative
approach for studying complex, multi-modal individual behavior jointly with emergent
group behavior is readily extensible to additional behavioral modes and their
neural correlates as well as to other species.
author:
- first_name: Roy
full_name: Harpaz, Roy
last_name: Harpaz
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing
predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154.
doi:10.1073/pnas.1703817114
apa: Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social
information processing predict individual behavior of fish in a group. PNAS.
National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114
chicago: Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social
Information Processing Predict Individual Behavior of Fish in a Group.” PNAS.
National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114.
ieee: R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information
processing predict individual behavior of fish in a group,” PNAS, vol.
114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.
ista: Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information
processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154.
mla: Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict
Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National
Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114.
short: R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154.
date_created: 2018-12-11T11:48:10Z
date_published: 2017-09-19T00:00:00Z
date_updated: 2021-01-12T08:12:36Z
day: '19'
department:
- _id: GaTk
doi: 10.1073/pnas.1703817114
external_id:
pmid:
- '28874581'
intvolume: ' 114'
issue: '38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/
month: '09'
oa: 1
oa_version: Submitted Version
page: 10149 - 10154
pmid: 1
publication: PNAS
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
publist_id: '6953'
quality_controlled: '1'
scopus_import: 1
status: public
title: Discrete modes of social information processing predict individual behavior
of fish in a group
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 114
year: '2017'
...
---
_id: '9709'
abstract:
- lang: eng
text: Across the nervous system, certain population spiking patterns are observed
far more frequently than others. A hypothesis about this structure is that these
collective activity patterns function as population codewords–collective modes–carrying
information distinct from that of any single cell. We investigate this phenomenon
in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop
a novel statistical model that decomposes the population response into modes;
it predicts the distribution of spiking activity in the ganglion cell population
with high accuracy. We found that the modes represent localized features of the
visual stimulus that are distinct from the features represented by single neurons.
Modes form clusters of activity states that are readily discriminated from one
another. When we repeated the same visual stimulus, we found that the same mode
was robustly elicited. These results suggest that retinal ganglion cells’ collective
signaling is endowed with a form of error-correcting code–a principle that may
hold in brain areas beyond retina.
article_processing_charge: No
author:
- first_name: Jason
full_name: Prentice, Jason
last_name: Prentice
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Mark
full_name: Ioffe, Mark
last_name: Ioffe
- first_name: Adrianna
full_name: Loback, Adrianna
last_name: Loback
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
citation:
ama: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Data from: Error-robust
modes of the retinal population code. 2017. doi:10.5061/dryad.1f1rc'
apa: 'Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M.
(2017). Data from: Error-robust modes of the retinal population code. Dryad. https://doi.org/10.5061/dryad.1f1rc'
chicago: 'Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik,
and Michael Berry. “Data from: Error-Robust Modes of the Retinal Population Code.”
Dryad, 2017. https://doi.org/10.5061/dryad.1f1rc.'
ieee: 'J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Data
from: Error-robust modes of the retinal population code.” Dryad, 2017.'
ista: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2017. Data from:
Error-robust modes of the retinal population code, Dryad, 10.5061/dryad.1f1rc.'
mla: 'Prentice, Jason, et al. Data from: Error-Robust Modes of the Retinal Population
Code. Dryad, 2017, doi:10.5061/dryad.1f1rc.'
short: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, (2017).
date_created: 2021-07-23T11:34:34Z
date_published: 2017-10-18T00:00:00Z
date_updated: 2023-02-21T16:34:41Z
day: '18'
department:
- _id: GaTk
doi: 10.5061/dryad.1f1rc
main_file_link:
- open_access: '1'
url: https://doi.org/10.5061/dryad.1f1rc
month: '10'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
record:
- id: '1197'
relation: used_in_publication
status: public
status: public
title: 'Data from: Error-robust modes of the retinal population code'
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '680'
abstract:
- lang: eng
text: In order to respond reliably to specific features of their environment, sensory
neurons need to integrate multiple incoming noisy signals. Crucially, they also
need to compete for the interpretation of those signals with other neurons representing
similar features. The form that this competition should take depends critically
on the noise corrupting these signals. In this study we show that for the type
of noise commonly observed in sensory systems, whose variance scales with the
mean signal, sensory neurons should selectively divide their input signals by
their predictions, suppressing ambiguous cues while amplifying others. Any change
in the stimulus context alters which inputs are suppressed, leading to a deep
dynamic reshaping of neural receptive fields going far beyond simple surround
suppression. Paradoxically, these highly variable receptive fields go alongside
and are in fact required for an invariant representation of external sensory features.
In addition to offering a normative account of context-dependent changes in sensory
responses, perceptual inference in the presence of signal-dependent noise accounts
for ubiquitous features of sensory neurons such as divisive normalization, gain
control and contrast dependent temporal dynamics.
article_number: e1005582
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Paul
full_name: Masset, Paul
last_name: Masset
- first_name: Boris
full_name: Gutkin, Boris
last_name: Gutkin
- first_name: Sophie
full_name: Denève, Sophie
last_name: Denève
citation:
ama: Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping
of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582
apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Sensory noise
predicts divisive reshaping of receptive fields. PLoS Computational Biology.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582
chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory
Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational
Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.
ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts
divisive reshaping of receptive fields,” PLoS Computational Biology, vol.
13, no. 6. Public Library of Science, 2017.
ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive
reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582.
mla: Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive
Fields.” PLoS Computational Biology, vol. 13, no. 6, e1005582, Public Library
of Science, 2017, doi:10.1371/journal.pcbi.1005582.
short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13
(2017).
date_created: 2018-12-11T11:47:53Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-02-23T14:10:54Z
day: '01'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005582
file:
- access_level: open_access
checksum: 796a1026076af6f4405a47d985bc7b68
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:07:47Z
date_updated: 2020-07-14T12:47:40Z
file_id: '4645'
file_name: IST-2017-898-v1+1_journal.pcbi.1005582.pdf
file_size: 14555676
relation: main_file
file_date_updated: 2020-07-14T12:47:40Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '7035'
pubrep_id: '898'
quality_controlled: '1'
related_material:
record:
- id: '9855'
relation: research_data
status: public
scopus_import: 1
status: public
title: Sensory noise predicts divisive reshaping of receptive fields
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2017'
...
---
_id: '9855'
abstract:
- lang: eng
text: Includes derivation of optimal estimation algorithm, generalisation to non-poisson
noise statistics, correlated input noise, and implementation of in a multi-layer
neural network.
article_processing_charge: No
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Paul
full_name: Masset, Paul
last_name: Masset
- first_name: Boris
full_name: Gutkin, Boris
last_name: Gutkin
- first_name: Sophie
full_name: Denève, Sophie
last_name: Denève
citation:
ama: Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001
apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Supplementary
appendix. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582.s001
chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Supplementary
Appendix.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.s001.
ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Supplementary appendix.”
Public Library of Science, 2017.
ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Supplementary appendix, Public
Library of Science, 10.1371/journal.pcbi.1005582.s001.
mla: Chalk, Matthew J., et al. Supplementary Appendix. Public Library of
Science, 2017, doi:10.1371/journal.pcbi.1005582.s001.
short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, (2017).
date_created: 2021-08-10T07:05:10Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-02-23T12:52:17Z
day: '01'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005582.s001
month: '06'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '680'
relation: used_in_publication
status: public
status: public
title: Supplementary appendix
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '666'
abstract:
- lang: eng
text: Antibiotics elicit drastic changes in microbial gene expression, including
the induction of stress response genes. While certain stress responses are known
to “cross-protect” bacteria from other stressors, it is unclear whether cellular
responses to antibiotics have a similar protective role. By measuring the genome-wide
transcriptional response dynamics of Escherichia coli to four antibiotics, we
found that trimethoprim induces a rapid acid stress response that protects bacteria
from subsequent exposure to acid. Combining microfluidics with time-lapse imaging
to monitor survival and acid stress response in single cells revealed that the
noisy expression of the acid resistance operon gadBC correlates with single-cell
survival. Cells with higher gadBC expression following trimethoprim maintain higher
intracellular pH and survive the acid stress longer. The seemingly random single-cell
survival under acid stress can therefore be predicted from gadBC expression and
rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap
for identifying the molecular mechanisms of single-cell cross-protection between
antibiotics and other stressors.
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts
subsequent single cell survival in an acidic environment. Cell Systems.
2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001
apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to
antibiotic stress predicts subsequent single cell survival in an acidic environment.
Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001
chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response
to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.”
Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001.
ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic
stress predicts subsequent single cell survival in an acidic environment,” Cell
Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.
ista: Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress
predicts subsequent single cell survival in an acidic environment. Cell Systems.
4(4), 393–403.
mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent
Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no.
4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001.
short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-26T00:00:00Z
date_updated: 2023-09-07T12:00:25Z
day: '26'
ddc:
- '576'
- '610'
department:
- _id: ToBo
- _id: GaTk
doi: 10.1016/j.cels.2017.03.001
ec_funded: 1
file:
- access_level: open_access
checksum: 04ff20011c3d9a601c514aa999a5fe1a
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:54Z
date_updated: 2020-07-14T12:47:35Z
file_id: '5041'
file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf
file_size: 2438660
relation: main_file
file_date_updated: 2020-07-14T12:47:35Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: 393 - 403
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
issn:
- '24054712'
publication_status: published
publisher: Cell Press
publist_id: '7061'
pubrep_id: '901'
quality_controlled: '1'
related_material:
record:
- id: '818'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Noisy response to antibiotic stress predicts subsequent single cell survival
in an acidic environment
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2017'
...
---
_id: '2016'
abstract:
- lang: eng
text: The Ising model is one of the simplest and most famous models of interacting
systems. It was originally proposed to model ferromagnetic interactions in statistical
physics and is now widely used to model spatial processes in many areas such as
ecology, sociology, and genetics, usually without testing its goodness-of-fit.
Here, we propose an exact goodness-of-fit test for the finite-lattice Ising model.
The theory of Markov bases has been developed in algebraic statistics for exact
goodness-of-fit testing using a Monte Carlo approach. However, this beautiful
theory has fallen short of its promise for applications, because finding a Markov
basis is usually computationally intractable. We develop a Monte Carlo method
for exact goodness-of-fit testing for the Ising model which avoids computing a
Markov basis and also leads to a better connectivity of the Markov chain and hence
to a faster convergence. We show how this method can be applied to analyze the
spatial organization of receptors on the cell membrane.
article_processing_charge: No
author:
- first_name: Abraham
full_name: Martin Del Campo Sanchez, Abraham
last_name: Martin Del Campo Sanchez
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Caroline
full_name: Uhler, Caroline
id: 49ADD78E-F248-11E8-B48F-1D18A9856A87
last_name: Uhler
orcid: 0000-0002-7008-0216
citation:
ama: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit
testing for the Ising model. Scandinavian Journal of Statistics. 2017;44(2):285-306.
doi:10.1111/sjos.12251
apa: Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., & Uhler, C. (2017).
Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of
Statistics. Wiley-Blackwell. https://doi.org/10.1111/sjos.12251
chicago: Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline
Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal
of Statistics. Wiley-Blackwell, 2017. https://doi.org/10.1111/sjos.12251.
ieee: A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit
testing for the Ising model,” Scandinavian Journal of Statistics, vol.
44, no. 2. Wiley-Blackwell, pp. 285–306, 2017.
ista: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit
testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306.
mla: Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for
the Ising Model.” Scandinavian Journal of Statistics, vol. 44, no. 2, Wiley-Blackwell,
2017, pp. 285–306, doi:10.1111/sjos.12251.
short: A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian
Journal of Statistics 44 (2017) 285–306.
date_created: 2018-12-11T11:55:13Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-09-19T15:13:27Z
day: '01'
department:
- _id: GaTk
doi: 10.1111/sjos.12251
external_id:
arxiv:
- '1410.1242'
isi:
- '000400985000001'
intvolume: ' 44'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1410.1242
month: '06'
oa: 1
oa_version: Preprint
page: 285 - 306
publication: Scandinavian Journal of Statistics
publication_identifier:
issn:
- '03036898'
publication_status: published
publisher: Wiley-Blackwell
publist_id: '5060'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Exact goodness-of-fit testing for the Ising model
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 44
year: '2017'
...
---
_id: '1104'
abstract:
- lang: eng
text: In the early visual system, cells of the same type perform the same computation
in different places of the visual field. How these cells code together a complex
visual scene is unclear. A common assumption is that cells of a single-type extract
a single-stimulus feature to form a feature map, but this has rarely been observed
directly. Using large-scale recordings in the rat retina, we show that a homogeneous
population of fast OFF ganglion cells simultaneously encodes two radically different
features of a visual scene. Cells close to a moving object code quasilinearly
for its position, while distant cells remain largely invariant to the object's
position and, instead, respond nonlinearly to changes in the object's speed. We
develop a quantitative model that accounts for this effect and identify a disinhibitory
circuit that mediates it. Ganglion cells of a single type thus do not code for
one, but two features simultaneously. This richer, flexible neural map might also
be present in other sensory systems.
article_number: '1964'
article_processing_charge: No
author:
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Ulisse
full_name: Ferrari, Ulisse
last_name: Ferrari
- first_name: Emilie
full_name: Mace, Emilie
last_name: Mace
- first_name: Pierre
full_name: Yger, Pierre
last_name: Yger
- first_name: Romain
full_name: Caplette, Romain
last_name: Caplette
- first_name: Serge
full_name: Picaud, Serge
last_name: Picaud
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
citation:
ama: Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion
cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y
apa: Deny, S., Ferrari, U., Mace, E., Yger, P., Caplette, R., Picaud, S., … Marre,
O. (2017). Multiplexed computations in retinal ganglion cells of a single type.
Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-02159-y
chicago: Deny, Stephane, Ulisse Ferrari, Emilie Mace, Pierre Yger, Romain Caplette,
Serge Picaud, Gašper Tkačik, and Olivier Marre. “Multiplexed Computations in Retinal
Ganglion Cells of a Single Type.” Nature Communications. Nature Publishing
Group, 2017. https://doi.org/10.1038/s41467-017-02159-y.
ieee: S. Deny et al., “Multiplexed computations in retinal ganglion cells
of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing
Group, 2017.
ista: Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkačik G, Marre O.
2017. Multiplexed computations in retinal ganglion cells of a single type. Nature
Communications. 8(1), 1964.
mla: Deny, Stephane, et al. “Multiplexed Computations in Retinal Ganglion Cells
of a Single Type.” Nature Communications, vol. 8, no. 1, 1964, Nature Publishing
Group, 2017, doi:10.1038/s41467-017-02159-y.
short: S. Deny, U. Ferrari, E. Mace, P. Yger, R. Caplette, S. Picaud, G. Tkačik,
O. Marre, Nature Communications 8 (2017).
date_created: 2018-12-11T11:50:10Z
date_published: 2017-12-06T00:00:00Z
date_updated: 2023-09-20T11:41:19Z
day: '06'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1038/s41467-017-02159-y
ec_funded: 1
external_id:
isi:
- '000417241200004'
file:
- access_level: open_access
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:06Z
date_updated: 2018-12-12T10:16:06Z
file_id: '5191'
file_name: IST-2018-921-v1+1_s41467-017-02159-y.pdf
file_size: 2872887
relation: main_file
file_date_updated: 2018-12-12T10:16:06Z
has_accepted_license: '1'
intvolume: ' 8'
isi: 1
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25CD3DD2-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '604102'
name: Localization of ion channels and receptors by two and three-dimensional immunoelectron
microscopic approaches
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '6266'
pubrep_id: '921'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multiplexed computations in retinal ganglion cells of a single type
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 8
year: '2017'
...
---
_id: '993'
abstract:
- lang: eng
text: In real-world applications, observations are often constrained to a small
fraction of a system. Such spatial subsampling can be caused by the inaccessibility
or the sheer size of the system, and cannot be overcome by longer sampling. Spatial
subsampling can strongly bias inferences about a system’s aggregated properties.
To overcome the bias, we derive analytically a subsampling scaling framework that
is applicable to different observables, including distributions of neuronal avalanches,
of number of people infected during an epidemic outbreak, and of node degrees.
We demonstrate how to infer the correct distributions of the underlying full system,
how to apply it to distinguish critical from subcritical systems, and how to disentangle
subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal
avalanche models and to recordings from developing neural networks. We show that
only mature, but not young networks follow power-law scaling, indicating self-organization
to criticality during development.
article_number: '15140'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Anna
full_name: Levina (Martius), Anna
id: 35AF8020-F248-11E8-B48F-1D18A9856A87
last_name: Levina (Martius)
- first_name: Viola
full_name: Priesemann, Viola
last_name: Priesemann
citation:
ama: Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications.
2017;8. doi:10.1038/ncomms15140
apa: Levina (Martius), A., & Priesemann, V. (2017). Subsampling scaling. Nature
Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms15140
chicago: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature
Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/ncomms15140.
ieee: A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications,
vol. 8. Nature Publishing Group, 2017.
ista: Levina (Martius) A, Priesemann V. 2017. Subsampling scaling. Nature Communications.
8, 15140.
mla: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature
Communications, vol. 8, 15140, Nature Publishing Group, 2017, doi:10.1038/ncomms15140.
short: A. Levina (Martius), V. Priesemann, Nature Communications 8 (2017).
date_created: 2018-12-11T11:49:35Z
date_published: 2017-05-04T00:00:00Z
date_updated: 2023-09-22T09:54:07Z
day: '04'
ddc:
- '005'
- '571'
department:
- _id: GaTk
- _id: JoCs
doi: 10.1038/ncomms15140
ec_funded: 1
external_id:
isi:
- '000400560700001'
file:
- access_level: open_access
checksum: 9880212f8c4c53404c7c6fbf9023c53a
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:15:05Z
date_updated: 2020-07-14T12:48:19Z
file_id: '5122'
file_name: IST-2017-819-v1+1_2017_Levina_SubsamplingScaling.pdf
file_size: 746224
relation: main_file
file_date_updated: 2020-07-14T12:48:19Z
has_accepted_license: '1'
intvolume: ' 8'
isi: 1
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '6406'
pubrep_id: '819'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Subsampling scaling
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 8
year: '2017'
...
---
_id: '955'
abstract:
- lang: eng
text: 'Gene expression is controlled by networks of regulatory proteins that interact
specifically with external signals and DNA regulatory sequences. These interactions
force the network components to co-evolve so as to continually maintain function.
Yet, existing models of evolution mostly focus on isolated genetic elements. In
contrast, we study the essential process by which regulatory networks grow: the
duplication and subsequent specialization of network components. We synthesize
a biophysical model of molecular interactions with the evolutionary framework
to find the conditions and pathways by which new regulatory functions emerge.
We show that specialization of new network components is usually slow, but can
be drastically accelerated in the presence of regulatory crosstalk and mutations
that promote promiscuous interactions between network components.'
article_number: '216'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions
on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1).
doi:10.1038/s41467-017-00238-8
apa: Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution
of new regulatory functions on biophysically realistic fitness landscapes. Nature
Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8
chicago: Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik.
“Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.”
Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8.
ieee: T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new
regulatory functions on biophysically realistic fitness landscapes,” Nature
Communications, vol. 8, no. 1. Nature Publishing Group, 2017.
ista: Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory
functions on biophysically realistic fitness landscapes. Nature Communications.
8(1), 216.
mla: Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically
Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216,
Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8.
short: T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications
8 (2017).
date_created: 2018-12-11T11:49:23Z
date_published: 2017-08-09T00:00:00Z
date_updated: 2023-09-22T10:00:49Z
day: '09'
ddc:
- '539'
- '576'
department:
- _id: GaTk
- _id: NiBa
doi: 10.1038/s41467-017-00238-8
ec_funded: 1
external_id:
isi:
- '000407198800005'
file:
- access_level: open_access
checksum: 29a1b5db458048d3bd5c67e0e2a56818
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:14Z
date_updated: 2020-07-14T12:48:16Z
file_id: '5064'
file_name: IST-2017-864-v1+1_s41467-017-00238-8.pdf
file_size: 998157
relation: main_file
- access_level: open_access
checksum: 7b78401e52a576cf3e6bbf8d0abadc17
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:15Z
date_updated: 2020-07-14T12:48:16Z
file_id: '5065'
file_name: IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf
file_size: 9715993
relation: main_file
file_date_updated: 2020-07-14T12:48:16Z
has_accepted_license: '1'
intvolume: ' 8'
isi: 1
issue: '1'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '6459'
pubrep_id: '864'
quality_controlled: '1'
related_material:
record:
- id: '6071'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Evolution of new regulatory functions on biophysically realistic fitness landscapes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 8
year: '2017'
...
---
_id: '959'
abstract:
- lang: eng
text: In this work it is shown that scale-free tails in metabolic flux distributions
inferred in stationary models are an artifact due to reactions involved in thermodynamically
unfeasible cycles, unbounded by physical constraints and in principle able to
perform work without expenditure of free energy. After implementing thermodynamic
constraints by removing such loops, metabolic flux distributions scale meaningfully
with the physical limiting factors, acquiring in turn a richer multimodal structure
potentially leading to symmetry breaking while optimizing for objective functions.
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: De Martino D. Scales and multimodal flux distributions in stationary metabolic
network models via thermodynamics. Physical Review E Statistical Nonlinear
and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419
apa: De Martino, D. (2017). Scales and multimodal flux distributions in stationary
metabolic network models via thermodynamics. Physical Review E Statistical
Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419
chicago: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary
Metabolic Network Models via Thermodynamics.” Physical Review E Statistical
Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419.
ieee: D. De Martino, “Scales and multimodal flux distributions in stationary metabolic
network models via thermodynamics,” Physical Review E Statistical Nonlinear
and Soft Matter Physics , vol. 95, no. 6. American Institute of Physics, p.
062419, 2017.
ista: De Martino D. 2017. Scales and multimodal flux distributions in stationary
metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear
and Soft Matter Physics . 95(6), 062419.
mla: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary
Metabolic Network Models via Thermodynamics.” Physical Review E Statistical
Nonlinear and Soft Matter Physics , vol. 95, no. 6, American Institute of
Physics, 2017, p. 062419, doi:10.1103/PhysRevE.95.062419.
short: D. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 95
(2017) 062419.
date_created: 2018-12-11T11:49:25Z
date_published: 2017-06-28T00:00:00Z
date_updated: 2023-09-22T09:59:01Z
day: '28'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.95.062419
ec_funded: 1
external_id:
isi:
- '000404546400004'
intvolume: ' 95'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/1703.00853.pdf
month: '06'
oa: 1
oa_version: Submitted Version
page: '062419'
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics '
publication_identifier:
issn:
- '24700045'
publication_status: published
publisher: American Institute of Physics
publist_id: '6446'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Scales and multimodal flux distributions in stationary metabolic network models
via thermodynamics
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 95
year: '2017'
...
---
_id: '947'
abstract:
- lang: eng
text: Viewing the ways a living cell can organize its metabolism as the phase space
of a physical system, regulation can be seen as the ability to reduce the entropy
of that space by selecting specific cellular configurations that are, in some
sense, optimal. Here we quantify the amount of regulation required to control
a cell's growth rate by a maximum-entropy approach to the space of underlying
metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern
as described by genome-scale models. We link the mean growth rate achieved by
a population of cells to the minimal amount of metabolic regulation needed to
achieve it through a phase diagram that highlights how growth suppression can
be as costly (in regulatory terms) as growth enhancement. Moreover, we provide
an interpretation of the inverse temperature β controlling maximum-entropy distributions
based on the underlying growth dynamics. Specifically, we show that the asymptotic
value of β for a cell population can be expected to depend on (i) the carrying
capacity of the environment, (ii) the initial size of the colony, and (iii) the
probability distribution from which the inoculum was sampled. Results obtained
for E. coli and human cells are found to be remarkably consistent with empirical
evidence.
article_number: '010401'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Fabrizio
full_name: Capuani, Fabrizio
last_name: Capuani
- first_name: Andrea
full_name: De Martino, Andrea
last_name: De Martino
citation:
ama: De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular
growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics
. 2017;96(1). doi:10.1103/PhysRevE.96.010401
apa: De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic
cost of cellular growth control. Physical Review E Statistical Nonlinear and
Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401
chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying
the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical
Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401.
ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost
of cellular growth control,” Physical Review E Statistical Nonlinear and Soft
Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017.
ista: De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost
of cellular growth control. Physical Review E Statistical Nonlinear and Soft
Matter Physics . 96(1), 010401.
mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth
Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics
, vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401.
short: D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical
Nonlinear and Soft Matter Physics 96 (2017).
date_created: 2018-12-11T11:49:21Z
date_published: 2017-07-10T00:00:00Z
date_updated: 2023-09-22T10:03:50Z
day: '10'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.96.010401
ec_funded: 1
external_id:
isi:
- '000405194200002'
intvolume: ' 96'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1703.00219
month: '07'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics '
publication_identifier:
issn:
- '24700045'
publication_status: published
publisher: American Institute of Physics
publist_id: '6470'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantifying the entropic cost of cellular growth control
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 96
year: '2017'
...
---
_id: '943'
abstract:
- lang: eng
text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel
morphogen gradients. To understand how these inputs are interpreted, we measured
morphogen signaling and target gene expression in mouse embryos and chick ex vivo
assays. From these data, we derived and validated a characteristic decoding map
that relates morphogen input to the positional identity of neural progenitors.
Analysis of the observed responses indicates that the underlying interpretation
strategy minimizes patterning errors in response to the joint input of noisy opposing
gradients. We reverse-engineered a transcriptional network that provides a mechanistic
basis for the observed cell fate decisions and accounts for the precision and
dynamics of pattern formation. Together, our data link opposing gradient dynamics
in a growing tissue to precise pattern formation.
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Yoji
full_name: Tabata, Yoji
last_name: Tabata
- first_name: Nathalie
full_name: Brandenberg, Nathalie
last_name: Brandenberg
- first_name: Matthias
full_name: Lutolf, Matthias
last_name: Lutolf
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
last_name: Bollenbach
- first_name: James
full_name: Briscoe, James
last_name: Briscoe
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing
neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383.
doi:10.1126/science.aam5887
apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach,
T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from
antiparallel morphogen gradients. Science. American Association for the
Advancement of Science. https://doi.org/10.1126/science.aam5887
chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf,
Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of
Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887.
ieee: M. P. Zagórski et al., “Decoding of position in the developing neural
tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345.
American Association for the Advancement of Science, pp. 1379–1383, 2017.
ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe
J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel
morphogen gradients. Science. 356(6345), 1379–1383.
mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural
Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345,
American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887.
short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach,
J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.
date_created: 2018-12-11T11:49:20Z
date_published: 2017-06-30T00:00:00Z
date_updated: 2023-09-26T15:38:05Z
day: '30'
department:
- _id: AnKi
- _id: GaTk
doi: 10.1126/science.aam5887
ec_funded: 1
external_id:
isi:
- '000404351500036'
pmid:
- '28663499'
intvolume: ' 356'
isi: 1
issue: '6345'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/
month: '06'
oa: 1
oa_version: Submitted Version
page: 1379 - 1383
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2524F500-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '201439'
name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '6474'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Decoding of position in the developing neural tube from antiparallel morphogen
gradients
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 356
year: '2017'
...
---
_id: '823'
abstract:
- lang: eng
text: The resolution of a linear system with positive integer variables is a basic
yet difficult computational problem with many applications. We consider sparse
uncorrelated random systems parametrised by the density c and the ratio α=N/M
between number of variables N and number of constraints M. By means of ensemble
calculations we show that the space of feasible solutions endows a Van-Der-Waals
phase diagram in the plane (c, α). We give numerical evidence that the associated
computational problems become more difficult across the critical point and in
particular in the coexistence region.
article_number: '093404'
article_processing_charge: No
author:
- first_name: Simona
full_name: Colabrese, Simona
last_name: Colabrese
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Luca
full_name: Leuzzi, Luca
last_name: Leuzzi
- first_name: Enzo
full_name: Marinari, Enzo
last_name: Marinari
citation:
ama: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer
linear problems. Journal of Statistical Mechanics: Theory and Experiment.
2017;2017(9). doi:10.1088/1742-5468/aa85c3'
apa: 'Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase
transitions in integer linear problems. Journal of Statistical Mechanics:
Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3'
chicago: 'Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari.
“Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics:
Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.'
ieee: 'S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions
in integer linear problems,” Journal of Statistical Mechanics: Theory and
Experiment, vol. 2017, no. 9. IOPscience, 2017.'
ista: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions
in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment.
2017(9), 093404.'
mla: 'Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.”
Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no.
9, 093404, IOPscience, 2017, doi:10.1088/1742-5468/aa85c3.'
short: 'S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical
Mechanics: Theory and Experiment 2017 (2017).'
date_created: 2018-12-11T11:48:41Z
date_published: 2017-09-26T00:00:00Z
date_updated: 2023-09-26T16:18:12Z
day: '26'
department:
- _id: GaTk
doi: 10.1088/1742-5468/aa85c3
ec_funded: 1
external_id:
isi:
- '000411842900001'
intvolume: ' 2017'
isi: 1
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1705.06303
month: '09'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Journal of Statistical Mechanics: Theory and Experiment'
publication_identifier:
issn:
- '17425468'
publication_status: published
publisher: IOPscience
publist_id: '6826'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Phase transitions in integer linear problems
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '730'
abstract:
- lang: eng
text: Neural responses are highly structured, with population activity restricted
to a small subset of the astronomical range of possible activity patterns. Characterizing
these statistical regularities is important for understanding circuit computation,
but challenging in practice. Here we review recent approaches based on the maximum
entropy principle used for quantifying collective behavior in neural activity.
We highlight recent models that capture population-level statistics of neural
data, yielding insights into the organization of the neural code and its biological
substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing
surrogate ensembles that preserve aspects of the data, but are otherwise maximally
unstructured. This idea can be used to generate a hierarchy of controls against
which rigorous statistical tests are possible.
article_processing_charge: No
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural
controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001
apa: Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building
precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001
chicago: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for
Building Precise Neural Controls.” Current Opinion in Neurobiology. Elsevier,
2017. https://doi.org/10.1016/j.conb.2017.08.001.
ieee: C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise
neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp.
120–126, 2017.
ista: Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise
neural controls. Current Opinion in Neurobiology. 46, 120–126.
mla: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building
Precise Neural Controls.” Current Opinion in Neurobiology, vol. 46, Elsevier,
2017, pp. 120–26, doi:10.1016/j.conb.2017.08.001.
short: C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126.
date_created: 2018-12-11T11:48:11Z
date_published: 2017-10-01T00:00:00Z
date_updated: 2023-09-28T11:32:22Z
day: '01'
department:
- _id: GaTk
doi: 10.1016/j.conb.2017.08.001
ec_funded: 1
external_id:
isi:
- '000416196400016'
intvolume: ' 46'
isi: 1
language:
- iso: eng
month: '10'
oa_version: None
page: 120 - 126
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Current Opinion in Neurobiology
publication_identifier:
issn:
- '09594388'
publication_status: published
publisher: Elsevier
publist_id: '6943'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Maximum entropy models as a tool for building precise neural controls
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 46
year: '2017'
...
---
_id: '548'
abstract:
- lang: eng
text: In this work maximum entropy distributions in the space of steady states of
metabolic networks are considered upon constraining the first and second moments
of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux
distributions, emerges upon considering control on the average growth (optimization)
and its fluctuations (heterogeneity). This is applied to the carbon catabolic
core of Escherichia coli where it quantifies the metabolic activity of slow growing
phenotypes and it provides a quantitative map with metabolic fluxes, opening the
possibility to detect coexistence from flux data. A preliminary analysis on data
for E. coli cultures in standard conditions shows degeneracy for the inferred
parameters that extend in the coexistence region.
alternative_title:
- Rapid Communications
article_number: '060401'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: De Martino D. Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E.
2017;96(6). doi:10.1103/PhysRevE.96.060401
apa: De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E.
American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401
chicago: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by
Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical
Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401.
ieee: D. De Martino, “Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes,” Physical Review E,
vol. 96, no. 6. American Physical Society, 2017.
ista: De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6),
060401.
mla: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining
Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E,
vol. 96, no. 6, 060401, American Physical Society, 2017, doi:10.1103/PhysRevE.96.060401.
short: D. De Martino, Physical Review E 96 (2017).
date_created: 2018-12-11T11:47:06Z
date_published: 2017-12-21T00:00:00Z
date_updated: 2023-10-10T13:29:38Z
day: '21'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.96.060401
ec_funded: 1
intvolume: ' 96'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1707.00320
month: '12'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Review E
publication_identifier:
issn:
- 2470-0045
publication_status: published
publisher: American Physical Society
publist_id: '7266'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Maximum entropy modeling of metabolic networks by constraining growth-rate
moments predicts coexistence of phenotypes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 96
year: '2017'
...
---
_id: '1007'
abstract:
- lang: eng
text: 'A nonlinear system possesses an invariance with respect to a set of transformations
if its output dynamics remain invariant when transforming the input, and adjusting
the initial condition accordingly. Most research has focused on invariances with
respect to time-independent pointwise transformations like translational-invariance
(u(t) -> u(t) + p, p in R) or scale-invariance (u(t) -> pu(t), p in R>0).
In this article, we introduce the concept of s0-invariances with respect to continuous
input transformations exponentially growing/decaying over time. We show that s0-invariant
systems not only encompass linear time-invariant (LTI) systems with transfer functions
having an irreducible zero at s0 in R, but also that the input/output relationship
of nonlinear s0-invariant systems possesses properties well known from their linear
counterparts. Furthermore, we extend the concept of s0-invariances to second-
and higher-order s0-invariances, corresponding to invariances with respect to
transformations of the time-derivatives of the input, and encompassing LTI systems
with zeros of multiplicity two or higher. Finally, we show that nth-order 0-invariant
systems realize – under mild conditions – nth-order nonlinear differential operators:
when excited by an input of a characteristic functional form, the system’s output
converges to a constant value only depending on the nth (nonlinear) derivative
of the input.'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Eduardo
full_name: Sontag, Eduardo
last_name: Sontag
citation:
ama: Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica.
2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030
apa: Lang, M., & Sontag, E. (2017). Zeros of nonlinear systems with input invariances.
Automatica. International Federation of Automatic Control. https://doi.org/10.1016/j.automatica.2017.03.030
chicago: Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input
Invariances.” Automatica. International Federation of Automatic Control,
2017. https://doi.org/10.1016/j.automatica.2017.03.030.
ieee: M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,”
Automatica, vol. 81C. International Federation of Automatic Control, pp.
46–55, 2017.
ista: Lang M, Sontag E. 2017. Zeros of nonlinear systems with input invariances.
Automatica. 81C, 46–55.
mla: Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input Invariances.”
Automatica, vol. 81C, International Federation of Automatic Control, 2017,
pp. 46–55, doi:10.1016/j.automatica.2017.03.030.
short: M. Lang, E. Sontag, Automatica 81C (2017) 46–55.
date_created: 2018-12-11T11:49:39Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-10-17T08:51:18Z
day: '01'
ddc:
- '000'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1016/j.automatica.2017.03.030
ec_funded: 1
external_id:
isi:
- '000403513900006'
file:
- access_level: open_access
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:29Z
date_updated: 2018-12-12T10:11:29Z
file_id: '4884'
file_name: IST-2017-813-v1+1_ZerosOfNonlinearSystems.pdf
file_size: 1401954
relation: main_file
file_date_updated: 2018-12-12T10:11:29Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 46 - 55
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Automatica
publication_identifier:
issn:
- 0005-1098
publication_status: published
publisher: International Federation of Automatic Control
publist_id: '6391'
pubrep_id: '813'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Zeros of nonlinear systems with input invariances
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 81C
year: '2017'
...
---
_id: '665'
abstract:
- lang: eng
text: The molecular mechanisms underlying phenotypic variation in isogenic bacterial
populations remain poorly understood.We report that AcrAB-TolC, the main multidrug
efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell
poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex
formation. Mother cells inheriting old poles are phenotypically distinct and display
increased drug efflux activity relative to daughters. Consequently, we find systematic
and long-lived growth differences between mother and daughter cells in the presence
of subinhibitory drug concentrations. A simple model for biased partitioning predicts
a population structure of long-lived and highly heterogeneous phenotypes. This
straightforward mechanism of generating sustained growth rate differences at subinhibitory
antibiotic concentrations has implications for understanding the emergence of
multidrug resistance in bacteria.
article_processing_charge: No
article_type: original
author:
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Anna M
full_name: Andersson, Anna M
id: 2B8A40DA-F248-11E8-B48F-1D18A9856A87
last_name: Andersson
orcid: 0000-0003-2912-6769
- first_name: Kathrin
full_name: Tomasek, Kathrin
id: 3AEC8556-F248-11E8-B48F-1D18A9856A87
last_name: Tomasek
orcid: 0000-0003-3768-877X
- first_name: Enrique
full_name: Balleza, Enrique
last_name: Balleza
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug
efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science.
2017;356(6335):311-315. doi:10.1126/science.aaf4762
apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild,
R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB
TolC underlies long lived phenotypic heterogeneity. Science. American Association
for the Advancement of Science. https://doi.org/10.1126/science.aaf4762
chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza,
Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning
of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aaf4762.
ieee: T. Bergmiller et al., “Biased partitioning of the multidrug efflux
pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science,
vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315,
2017.
ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik
G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC
underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.
mla: Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump
AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science, vol.
356, no. 6335, American Association for the Advancement of Science, 2017, pp.
311–15, doi:10.1126/science.aaf4762.
short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild,
G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-21T00:00:00Z
date_updated: 2024-02-21T13:49:00Z
day: '21'
department:
- _id: CaGu
- _id: GaTk
- _id: Bio
doi: 10.1126/science.aaf4762
intvolume: ' 356'
issue: '6335'
language:
- iso: eng
month: '04'
oa_version: None
page: 311 - 315
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7064'
quality_controlled: '1'
related_material:
record:
- id: '5560'
relation: popular_science
status: public
scopus_import: 1
status: public
title: Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long
lived phenotypic heterogeneity
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 356
year: '2017'
...
---
_id: '735'
abstract:
- lang: eng
text: Cell-cell contact formation constitutes an essential step in evolution, leading
to the differentiation of specialized cell types. However, remarkably little is
known about whether and how the interplay between contact formation and fate specification
affects development. Here, we identify a positive feedback loop between cell-cell
contact duration, morphogen signaling, and mesendoderm cell-fate specification
during zebrafish gastrulation. We show that long-lasting cell-cell contacts enhance
the competence of prechordal plate (ppl) progenitor cells to respond to Nodal
signaling, required for ppl cell-fate specification. We further show that Nodal
signaling promotes ppl cell-cell contact duration, generating a positive feedback
loop between ppl cell-cell contact duration and cell-fate specification. Finally,
by combining mathematical modeling and experimentation, we show that this feedback
determines whether anterior axial mesendoderm cells become ppl or, instead, turn
into endoderm. Thus, the interdependent activities of cell-cell signaling and
contact formation control fate diversification within the developing embryo.
article_processing_charge: No
author:
- first_name: Vanessa
full_name: Barone, Vanessa
id: 419EECCC-F248-11E8-B48F-1D18A9856A87
last_name: Barone
orcid: 0000-0003-2676-3367
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Gabriel
full_name: Krens, Gabriel
id: 2B819732-F248-11E8-B48F-1D18A9856A87
last_name: Krens
orcid: 0000-0003-4761-5996
- first_name: Saurabh
full_name: Pradhan, Saurabh
last_name: Pradhan
- first_name: Shayan
full_name: Shamipour, Shayan
id: 40B34FE2-F248-11E8-B48F-1D18A9856A87
last_name: Shamipour
- first_name: Keisuke
full_name: Sako, Keisuke
id: 3BED66BE-F248-11E8-B48F-1D18A9856A87
last_name: Sako
orcid: 0000-0002-6453-8075
- first_name: Mateusz K
full_name: Sikora, Mateusz K
id: 2F74BCDE-F248-11E8-B48F-1D18A9856A87
last_name: Sikora
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Carl-Philipp J
full_name: Heisenberg, Carl-Philipp J
id: 39427864-F248-11E8-B48F-1D18A9856A87
last_name: Heisenberg
orcid: 0000-0002-0912-4566
citation:
ama: Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell
contact duration and morphogen signaling determines cell fate. Developmental
Cell. 2017;43(2):198-211. doi:10.1016/j.devcel.2017.09.014
apa: Barone, V., Lang, M., Krens, G., Pradhan, S., Shamipour, S., Sako, K., … Heisenberg,
C.-P. J. (2017). An effective feedback loop between cell-cell contact duration
and morphogen signaling determines cell fate. Developmental Cell. Cell
Press. https://doi.org/10.1016/j.devcel.2017.09.014
chicago: Barone, Vanessa, Moritz Lang, Gabriel Krens, Saurabh Pradhan, Shayan Shamipour,
Keisuke Sako, Mateusz K Sikora, Calin C Guet, and Carl-Philipp J Heisenberg. “An
Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling
Determines Cell Fate.” Developmental Cell. Cell Press, 2017. https://doi.org/10.1016/j.devcel.2017.09.014.
ieee: V. Barone et al., “An effective feedback loop between cell-cell contact
duration and morphogen signaling determines cell fate,” Developmental Cell,
vol. 43, no. 2. Cell Press, pp. 198–211, 2017.
ista: Barone V, Lang M, Krens G, Pradhan S, Shamipour S, Sako K, Sikora MK, Guet
CC, Heisenberg C-PJ. 2017. An effective feedback loop between cell-cell contact
duration and morphogen signaling determines cell fate. Developmental Cell. 43(2),
198–211.
mla: Barone, Vanessa, et al. “An Effective Feedback Loop between Cell-Cell Contact
Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell,
vol. 43, no. 2, Cell Press, 2017, pp. 198–211, doi:10.1016/j.devcel.2017.09.014.
short: V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora,
C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211.
date_created: 2018-12-11T11:48:13Z
date_published: 2017-10-23T00:00:00Z
date_updated: 2024-03-28T23:30:39Z
day: '23'
department:
- _id: CaHe
- _id: CaGu
- _id: GaTk
doi: 10.1016/j.devcel.2017.09.014
ec_funded: 1
external_id:
isi:
- '000413443700011'
intvolume: ' 43'
isi: 1
issue: '2'
language:
- iso: eng
month: '10'
oa_version: None
page: 198 - 211
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 252DD2A6-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I2058
name: 'Cell segregation in gastrulation: the role of cell fate specification'
publication: Developmental Cell
publication_identifier:
issn:
- '15345807'
publication_status: published
publisher: Cell Press
publist_id: '6934'
quality_controlled: '1'
related_material:
record:
- id: '961'
relation: dissertation_contains
status: public
- id: '8350'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: An effective feedback loop between cell-cell contact duration and morphogen
signaling determines cell fate
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 43
year: '2017'
...
---
_id: '1082'
abstract:
- lang: eng
text: In many applications, it is desirable to extract only the relevant aspects
of data. A principled way to do this is the information bottleneck (IB) method,
where one seeks a code that maximises information about a relevance variable,
Y, while constraining the information encoded about the original data, X. Unfortunately
however, the IB method is computationally demanding when data are high-dimensional
and/or non-gaussian. Here we propose an approximate variational scheme for maximising
a lower bound on the IB objective, analogous to variational EM. Using this method,
we derive an IB algorithm to recover features that are both relevant and sparse.
Finally, we demonstrate how kernelised versions of the algorithm can be used to
address a broad range of problems with non-linear relation between X and Y.
alternative_title:
- Advances in Neural Information Processing Systems
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: 'Chalk MJ, Marre O, Tkačik G. Relevant sparse codes with variational information
bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973.'
apa: 'Chalk, M. J., Marre, O., & Tkačik, G. (2016). Relevant sparse codes with
variational information bottleneck (Vol. 29, pp. 1965–1973). Presented at the
NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information
Processing Systems.'
chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Relevant Sparse Codes
with Variational Information Bottleneck,” 29:1965–73. Neural Information Processing
Systems, 2016.
ieee: 'M. J. Chalk, O. Marre, and G. Tkačik, “Relevant sparse codes with variational
information bottleneck,” presented at the NIPS: Neural Information Processing
Systems, Barcelona, Spain, 2016, vol. 29, pp. 1965–1973.'
ista: 'Chalk MJ, Marre O, Tkačik G. 2016. Relevant sparse codes with variational
information bottleneck. NIPS: Neural Information Processing Systems, Advances
in Neural Information Processing Systems, vol. 29, 1965–1973.'
mla: Chalk, Matthew J., et al. Relevant Sparse Codes with Variational Information
Bottleneck. Vol. 29, Neural Information Processing Systems, 2016, pp. 1965–73.
short: M.J. Chalk, O. Marre, G. Tkačik, in:, Neural Information Processing Systems,
2016, pp. 1965–1973.
conference:
end_date: 2016-12-10
location: Barcelona, Spain
name: 'NIPS: Neural Information Processing Systems'
start_date: 2016-12-05
date_created: 2018-12-11T11:50:03Z
date_published: 2016-12-01T00:00:00Z
date_updated: 2021-01-12T06:48:09Z
day: '01'
department:
- _id: GaTk
intvolume: ' 29'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1605.07332
month: '12'
oa: 1
oa_version: Preprint
page: 1965-1973
publication_status: published
publisher: Neural Information Processing Systems
publist_id: '6298'
quality_controlled: '1'
related_material:
link:
- relation: other
url: https://papers.nips.cc/paper/6101-relevant-sparse-codes-with-variational-information-bottleneck
scopus_import: 1
status: public
title: Relevant sparse codes with variational information bottleneck
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 29
year: '2016'
...
---
_id: '1105'
abstract:
- lang: eng
text: Jointly characterizing neural responses in terms of several external variables
promises novel insights into circuit function, but remains computationally prohibitive
in practice. Here we use gaussian process (GP) priors and exploit recent advances
in fast GP inference and learning based on Kronecker methods, to efficiently estimate
multidimensional nonlinear tuning functions. Our estimator require considerably
less data than traditional methods and further provides principled uncertainty
estimates. We apply these tools to hippocampal recordings during open field exploration
and use them to characterize the joint dependence of CA1 responses on the position
of the animal and several other variables, including the animal\'s speed, direction
of motion, and network oscillations.Our results provide an unprecedentedly detailed
quantification of the tuning of hippocampal neurons. The model\'s generality suggests
that our approach can be used to estimate neural response properties in other
brain regions.
acknowledgement: "We thank Jozsef Csicsvari for kindly sharing the CA1 data.\r\nThis
work was supported by the People Programme (Marie Curie Actions) of the European
Union’s Seventh Framework Programme(FP7/2007-2013) under REA grant agreement no.
291734."
alternative_title:
- Advances in Neural Information Processing Systems
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: 'Savin C, Tkačik G. Estimating nonlinear neural response functions using GP
priors and Kronecker methods. In: Vol 29. Neural Information Processing Systems;
2016:3610-3618.'
apa: 'Savin, C., & Tkačik, G. (2016). Estimating nonlinear neural response functions
using GP priors and Kronecker methods (Vol. 29, pp. 3610–3618). Presented at the
NIPS: Neural Information Processing Systems, Barcelona; Spain: Neural Information
Processing Systems.'
chicago: Savin, Cristina, and Gašper Tkačik. “Estimating Nonlinear Neural Response
Functions Using GP Priors and Kronecker Methods,” 29:3610–18. Neural Information
Processing Systems, 2016.
ieee: 'C. Savin and G. Tkačik, “Estimating nonlinear neural response functions using
GP priors and Kronecker methods,” presented at the NIPS: Neural Information Processing
Systems, Barcelona; Spain, 2016, vol. 29, pp. 3610–3618.'
ista: 'Savin C, Tkačik G. 2016. Estimating nonlinear neural response functions using
GP priors and Kronecker methods. NIPS: Neural Information Processing Systems,
Advances in Neural Information Processing Systems, vol. 29, 3610–3618.'
mla: Savin, Cristina, and Gašper Tkačik. Estimating Nonlinear Neural Response
Functions Using GP Priors and Kronecker Methods. Vol. 29, Neural Information
Processing Systems, 2016, pp. 3610–18.
short: C. Savin, G. Tkačik, in:, Neural Information Processing Systems, 2016, pp.
3610–3618.
conference:
end_date: 2016-12-10
location: Barcelona; Spain
name: 'NIPS: Neural Information Processing Systems'
start_date: 2016-12-05
date_created: 2018-12-11T11:50:10Z
date_published: 2016-12-01T00:00:00Z
date_updated: 2021-01-12T06:48:19Z
day: '01'
department:
- _id: GaTk
ec_funded: 1
intvolume: ' 29'
language:
- iso: eng
main_file_link:
- url: http://papers.nips.cc/paper/6153-estimating-nonlinear-neural-response-functions-using-gp-priors-and-kronecker-methods
month: '12'
oa_version: None
page: 3610-3618
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication_status: published
publisher: Neural Information Processing Systems
publist_id: '6265'
quality_controlled: '1'
scopus_import: 1
status: public
title: Estimating nonlinear neural response functions using GP priors and Kronecker
methods
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 29
year: '2016'
...
---
_id: '1170'
abstract:
- lang: eng
text: The increasing complexity of dynamic models in systems and synthetic biology
poses computational challenges especially for the identification of model parameters.
While modularization of the corresponding optimization problems could help reduce
the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit
a simple decomposition of most biomolecular networks into subnetworks, or modules.
Drawing on ideas from network modularization and multiple-shooting optimization,
we present here a modular parameter identification approach that explicitly allows
for such interdependencies. Interfaces between our modules are given by the experimentally
measured molecular species. This definition allows deriving good (initial) estimates
for the inter-module communication directly from the experimental data. Given
these estimates, the states and parameter sensitivities of different modules can
be integrated independently. To achieve consistency between modules, we iteratively
adjust the estimates for inter-module communication while optimizing the parameters.
After convergence to an optimal parameter set---but not during earlier iterations---the
intermodule communication as well as the individual modules\' state dynamics agree
with the dynamics of the nonmodularized network. Our modular parameter identification
approach allows for easy parallelization; it can reduce the computational complexity
for larger networks and decrease the probability to converge to suboptimal local
minima. We demonstrate the algorithm\'s performance in parameter estimation for
two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling
pathway.
author:
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Jörg
full_name: Stelling, Jörg
last_name: Stelling
citation:
ama: Lang M, Stelling J. Modular parameter identification of biomolecular networks.
SIAM Journal on Scientific Computing. 2016;38(6):B988-B1008. doi:10.1137/15M103306X
apa: Lang, M., & Stelling, J. (2016). Modular parameter identification of biomolecular
networks. SIAM Journal on Scientific Computing. Society for Industrial
and Applied Mathematics . https://doi.org/10.1137/15M103306X
chicago: Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular
Networks.” SIAM Journal on Scientific Computing. Society for Industrial
and Applied Mathematics , 2016. https://doi.org/10.1137/15M103306X.
ieee: M. Lang and J. Stelling, “Modular parameter identification of biomolecular
networks,” SIAM Journal on Scientific Computing, vol. 38, no. 6. Society
for Industrial and Applied Mathematics , pp. B988–B1008, 2016.
ista: Lang M, Stelling J. 2016. Modular parameter identification of biomolecular
networks. SIAM Journal on Scientific Computing. 38(6), B988–B1008.
mla: Lang, Moritz, and Jörg Stelling. “Modular Parameter Identification of Biomolecular
Networks.” SIAM Journal on Scientific Computing, vol. 38, no. 6, Society
for Industrial and Applied Mathematics , 2016, pp. B988–1008, doi:10.1137/15M103306X.
short: M. Lang, J. Stelling, SIAM Journal on Scientific Computing 38 (2016) B988–B1008.
date_created: 2018-12-11T11:50:31Z
date_published: 2016-11-15T00:00:00Z
date_updated: 2021-01-12T06:48:49Z
day: '15'
ddc:
- '003'
- '518'
- '570'
- '621'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1137/15M103306X
file:
- access_level: local
checksum: 781bc3ffd30b2dd65b7727c5a285fc78
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:41Z
date_updated: 2020-07-14T12:44:37Z
file_id: '5095'
file_name: IST-2017-811-v1+1_modular_parameter_identification.pdf
file_size: 871964
relation: main_file
file_date_updated: 2020-07-14T12:44:37Z
has_accepted_license: '1'
intvolume: ' 38'
issue: '6'
language:
- iso: eng
month: '11'
oa_version: Submitted Version
page: B988 - B1008
publication: SIAM Journal on Scientific Computing
publication_status: published
publisher: 'Society for Industrial and Applied Mathematics '
publist_id: '6186'
pubrep_id: '811'
quality_controlled: '1'
scopus_import: 1
status: public
title: Modular parameter identification of biomolecular networks
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 38
year: '2016'
...
---
_id: '1171'
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: 'Tkačik G. Understanding regulatory networks requires more than computing a
multitude of graph statistics: Comment on "Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function"
by O. C. Martin et al. Physics of Life Reviews. 2016;17:166-167. doi:10.1016/j.plrev.2016.06.005'
apa: 'Tkačik, G. (2016). Understanding regulatory networks requires more than computing
a multitude of graph statistics: Comment on "Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function"
by O. C. Martin et al. Physics of Life Reviews. Elsevier. https://doi.org/10.1016/j.plrev.2016.06.005'
chicago: 'Tkačik, Gašper. “Understanding Regulatory Networks Requires More than
Computing a Multitude of Graph Statistics: Comment on "Drivers of Structural
Features in Gene Regulatory Networks: From Biophysical Constraints to Biological
Function" by O. C. Martin et Al.” Physics of Life Reviews. Elsevier,
2016. https://doi.org/10.1016/j.plrev.2016.06.005.'
ieee: 'G. Tkačik, “Understanding regulatory networks requires more than computing
a multitude of graph statistics: Comment on "Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function"
by O. C. Martin et al.,” Physics of Life Reviews, vol. 17. Elsevier, pp.
166–167, 2016.'
ista: 'Tkačik G. 2016. Understanding regulatory networks requires more than computing
a multitude of graph statistics: Comment on "Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function"
by O. C. Martin et al. Physics of Life Reviews. 17, 166–167.'
mla: 'Tkačik, Gašper. “Understanding Regulatory Networks Requires More than Computing
a Multitude of Graph Statistics: Comment on "Drivers of Structural Features
in Gene Regulatory Networks: From Biophysical Constraints to Biological Function"
by O. C. Martin et Al.” Physics of Life Reviews, vol. 17, Elsevier, 2016,
pp. 166–67, doi:10.1016/j.plrev.2016.06.005.'
short: G. Tkačik, Physics of Life Reviews 17 (2016) 166–167.
date_created: 2018-12-11T11:50:32Z
date_published: 2016-07-01T00:00:00Z
date_updated: 2021-01-12T06:48:50Z
day: '01'
department:
- _id: GaTk
doi: 10.1016/j.plrev.2016.06.005
intvolume: ' 17'
language:
- iso: eng
month: '07'
oa_version: None
page: 166 - 167
publication: Physics of Life Reviews
publication_status: published
publisher: Elsevier
publist_id: '6185'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Understanding regulatory networks requires more than computing a multitude
of graph statistics: Comment on "Drivers of structural features in gene regulatory
networks: From biophysical constraints to biological function" by O. C. Martin
et al.'
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2016'
...
---
_id: '1188'
abstract:
- lang: eng
text: "We consider a population dynamics model coupling cell growth to a diffusion
in the space of metabolic phenotypes as it can be obtained from realistic constraints-based
modelling. \r\nIn the asymptotic regime of slow\r\ndiffusion, that coincides with
the relevant experimental range, the resulting\r\nnon-linear Fokker–Planck equation
is solved for the steady state in the WKB\r\napproximation that maps it into the
ground state of a quantum particle in an\r\nAiry potential plus a centrifugal
term. We retrieve scaling laws for growth rate\r\nfluctuations and time response
with respect to the distance from the maximum\r\ngrowth rate suggesting that suboptimal
populations can have a faster response\r\nto perturbations."
acknowledgement: D De Martino is supported by the People Programme (Marie Curie Actions)
of the European Union's Seventh Framework Programme (FP7/2007–2013) under REA grant
agreement no. [291734]. D Masoero is supported by the FCT scholarship, number SFRH/BPD/75908/2011.
D De Martino thanks the Grupo de Física Matemática of the Universidade de Lisboa
for the kind hospitality. We also wish to thank Matteo Osella, Vincenzo Vitagliano
and Vera Luz Masoero for useful discussions, also late at night.
article_number: '123502'
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Davide
full_name: Masoero, Davide
last_name: Masoero
citation:
ama: 'De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization,
applied to metabolism & growth. Journal of Statistical Mechanics:
Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f'
apa: 'De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness
maximization, applied to metabolism & growth. Journal of Statistical
Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa4e8f'
chicago: 'De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy
Fitness Maximization, Applied to Metabolism & Growth.” Journal of
Statistical Mechanics: Theory and Experiment. IOPscience, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.'
ieee: 'D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization,
applied to metabolism & growth,” Journal of Statistical Mechanics:
Theory and Experiment, vol. 2016, no. 12. IOPscience, 2016.'
ista: 'De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization,
applied to metabolism & growth. Journal of Statistical Mechanics: Theory
and Experiment. 2016(12), 123502.'
mla: 'De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness
Maximization, Applied to Metabolism & Growth.” Journal of Statistical
Mechanics: Theory and Experiment, vol. 2016, no. 12, 123502, IOPscience, 2016,
doi:10.1088/1742-5468/aa4e8f.'
short: 'D. De Martino, D. Masoero, Journal of Statistical Mechanics: Theory and
Experiment 2016 (2016).'
date_created: 2018-12-11T11:50:37Z
date_published: 2016-12-30T00:00:00Z
date_updated: 2021-01-12T06:48:57Z
day: '30'
department:
- _id: GaTk
doi: 10.1088/1742-5468/aa4e8f
ec_funded: 1
intvolume: ' 2016'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1606.09048
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Journal of Statistical Mechanics: Theory and Experiment'
publication_status: published
publisher: IOPscience
publist_id: '6165'
quality_controlled: '1'
scopus_import: 1
status: public
title: Asymptotic analysis of noisy fitness maximization, applied to metabolism &
growth
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 2016
year: '2016'
...
---
_id: '1203'
abstract:
- lang: eng
text: Haemophilus haemolyticus has been recently discovered to have the potential
to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae
(NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified
because none of the existing tests targeting the known phenotypes of H. haemolyticus
are able to specifically identify H. haemolyticus. Through comparative genomic
analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to
H. haemolyticus that can be used as targets for the identification of H. haemolyticus.
A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase
2 in the purine synthesis pathway) was developed and evaluated. The lower limit
of detection was 40 genomes/PCR; the sensitivity and specificity in detecting
H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination
of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets
(H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was
also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification
of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification
of H. influenzae, respectively. The dual-target testing scheme can be used for
the diagnosis and surveillance of infection and disease caused by H. haemolyticus
and NT H. influenzae.
acknowledgement: We are grateful to ABCs for providing strains and the Bacterial Meningitis
Laboratory for technical support.
author:
- first_name: Fang
full_name: Hu, Fang
last_name: Hu
- first_name: Lavanya
full_name: Rishishwar, Lavanya
last_name: Rishishwar
- first_name: Ambily
full_name: Sivadas, Ambily
last_name: Sivadas
- first_name: Gabriel
full_name: Mitchell, Gabriel
id: 315BCD80-F248-11E8-B48F-1D18A9856A87
last_name: Mitchell
- first_name: Jordan
full_name: King, Jordan
last_name: King
- first_name: Timothy
full_name: Murphy, Timothy
last_name: Murphy
- first_name: Janet
full_name: Gilsdorf, Janet
last_name: Gilsdorf
- first_name: Leonard
full_name: Mayer, Leonard
last_name: Mayer
- first_name: Xin
full_name: Wang, Xin
last_name: Wang
citation:
ama: Hu F, Rishishwar L, Sivadas A, et al. Comparative genomic analysis of Haemophilus
haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for
their discrimination. Journal of Clinical Microbiology. 2016;54(12):3010-3017.
doi:10.1128/JCM.01511-16
apa: Hu, F., Rishishwar, L., Sivadas, A., Mitchell, G., King, J., Murphy, T., …
Wang, X. (2016). Comparative genomic analysis of Haemophilus haemolyticus and
nontypeable Haemophilus influenzae and a new testing scheme for their discrimination.
Journal of Clinical Microbiology. American Society for Microbiology. https://doi.org/10.1128/JCM.01511-16
chicago: Hu, Fang, Lavanya Rishishwar, Ambily Sivadas, Gabriel Mitchell, Jordan
King, Timothy Murphy, Janet Gilsdorf, Leonard Mayer, and Xin Wang. “Comparative
Genomic Analysis of Haemophilus Haemolyticus and Nontypeable Haemophilus Influenzae
and a New Testing Scheme for Their Discrimination.” Journal of Clinical Microbiology.
American Society for Microbiology, 2016. https://doi.org/10.1128/JCM.01511-16.
ieee: F. Hu et al., “Comparative genomic analysis of Haemophilus haemolyticus
and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination,”
Journal of Clinical Microbiology, vol. 54, no. 12. American Society for
Microbiology, pp. 3010–3017, 2016.
ista: Hu F, Rishishwar L, Sivadas A, Mitchell G, King J, Murphy T, Gilsdorf J, Mayer
L, Wang X. 2016. Comparative genomic analysis of Haemophilus haemolyticus and
nontypeable Haemophilus influenzae and a new testing scheme for their discrimination.
Journal of Clinical Microbiology. 54(12), 3010–3017.
mla: Hu, Fang, et al. “Comparative Genomic Analysis of Haemophilus Haemolyticus
and Nontypeable Haemophilus Influenzae and a New Testing Scheme for Their Discrimination.”
Journal of Clinical Microbiology, vol. 54, no. 12, American Society for
Microbiology, 2016, pp. 3010–17, doi:10.1128/JCM.01511-16.
short: F. Hu, L. Rishishwar, A. Sivadas, G. Mitchell, J. King, T. Murphy, J. Gilsdorf,
L. Mayer, X. Wang, Journal of Clinical Microbiology 54 (2016) 3010–3017.
date_created: 2018-12-11T11:50:41Z
date_published: 2016-12-01T00:00:00Z
date_updated: 2021-01-12T06:49:04Z
day: '01'
department:
- _id: GaTk
doi: 10.1128/JCM.01511-16
intvolume: ' 54'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121393/
month: '12'
oa: 1
oa_version: Submitted Version
page: 3010 - 3017
publication: Journal of Clinical Microbiology
publication_status: published
publisher: American Society for Microbiology
publist_id: '6146'
quality_controlled: '1'
scopus_import: 1
status: public
title: Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus
influenzae and a new testing scheme for their discrimination
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 54
year: '2016'
...
---
_id: '1214'
abstract:
- lang: eng
text: 'With the accelerated development of robot technologies, optimal control becomes
one of the central themes of research. In traditional approaches, the controller,
by its internal functionality, finds appropriate actions on the basis of the history
of sensor values, guided by the goals, intentions, objectives, learning schemes,
and so forth. While very successful with classical robots, these methods run into
severe difficulties when applied to soft robots, a new field of robotics with
large interest for human-robot interaction. We claim that a novel controller paradigm
opens new perspective for this field. This paper applies a recently developed
neuro controller with differential extrinsic synaptic plasticity to a muscle-tendon
driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we
observe a vast variety of self-organized behavior patterns: when left alone, the
arm realizes pseudo-random sequences of different poses. By applying physical
forces, the system can be entrained into definite motion patterns like wiping
a table. Most interestingly, after attaching an object, the controller gets in
a functional resonance with the object''s internal dynamics, starting to shake
spontaneously bottles half-filled with water or sensitively driving an attached
pendulum into a circular mode. When attached to the crank of a wheel the neural
system independently develops to rotate it. In this way, the robot discovers affordances
of objects its body is interacting with.'
acknowledgement: RD thanks for the hospitality at the Max-Planck-Institute and for
helpful discussions with Nihat Ay and Keyan Zahedi.
article_number: '7759138'
author:
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
- first_name: Raphael
full_name: Hostettler, Raphael
last_name: Hostettler
- first_name: Alois
full_name: Knoll, Alois
last_name: Knoll
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
citation:
ama: 'Martius GS, Hostettler R, Knoll A, Der R. Compliant control for soft robots:
Emergent behavior of a tendon driven anthropomorphic arm. In: Vol 2016-November.
IEEE; 2016. doi:10.1109/IROS.2016.7759138'
apa: 'Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant
control for soft robots: Emergent behavior of a tendon driven anthropomorphic
arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on
Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138'
chicago: 'Martius, Georg S, Raphael Hostettler, Alois Knoll, and Ralf Der. “Compliant
Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic
Arm,” Vol. 2016–November. IEEE, 2016. https://doi.org/10.1109/IROS.2016.7759138.'
ieee: 'G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Compliant control for
soft robots: Emergent behavior of a tendon driven anthropomorphic arm,” presented
at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS
, Daejeon, Korea, 2016, vol. 2016–November.'
ista: 'Martius GS, Hostettler R, Knoll A, Der R. 2016. Compliant control for soft
robots: Emergent behavior of a tendon driven anthropomorphic arm. IEEE RSJ International
Conference on Intelligent Robots and Systems IROS vol. 2016–November, 7759138.'
mla: 'Martius, Georg S., et al. Compliant Control for Soft Robots: Emergent Behavior
of a Tendon Driven Anthropomorphic Arm. Vol. 2016–November, 7759138, IEEE,
2016, doi:10.1109/IROS.2016.7759138.'
short: G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016.
conference:
end_date: 2016-09-14
location: Daejeon, Korea
name: 'IEEE RSJ International Conference on Intelligent Robots and Systems IROS '
start_date: 2016-09-09
date_created: 2018-12-11T11:50:45Z
date_published: 2016-11-28T00:00:00Z
date_updated: 2021-01-12T06:49:08Z
day: '28'
department:
- _id: ChLa
- _id: GaTk
doi: 10.1109/IROS.2016.7759138
language:
- iso: eng
month: '11'
oa_version: None
publication_status: published
publisher: IEEE
publist_id: '6121'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic
arm'
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 2016-November
year: '2016'
...
---
_id: '1220'
abstract:
- lang: eng
text: Theoretical and numerical aspects of aerodynamic efficiency of propulsion
systems coupled to the boundary layer of a fuselage are studied. We discuss the
effects of local flow fields, which are affected both by conservative flow acceleration
as well as total pressure losses, on the efficiency of boundary layer immersed
propulsion devices. We introduce the concept of a boundary layer retardation turbine
that helps reduce skin friction over the fuselage. We numerically investigate
efficiency gains offered by boundary layer and wake interacting devices. We discuss
the results in terms of a total energy consumption framework and show that efficiency
gains of any device depend on all the other elements of the propulsion system.
author:
- first_name: Gregor
full_name: Mikić, Gregor
last_name: Mikić
- first_name: Alex
full_name: Stoll, Alex
last_name: Stoll
- first_name: Joe
full_name: Bevirt, Joe
last_name: Bevirt
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Mark
full_name: Moore, Mark
last_name: Moore
citation:
ama: 'Mikić G, Stoll A, Bevirt J, Grah R, Moore M. Fuselage boundary layer ingestion
propulsion applied to a thin haul commuter aircraft for optimal efficiency. In:
AIAA; 2016:1-19. doi:10.2514/6.2016-3764'
apa: 'Mikić, G., Stoll, A., Bevirt, J., Grah, R., & Moore, M. (2016). Fuselage
boundary layer ingestion propulsion applied to a thin haul commuter aircraft for
optimal efficiency (pp. 1–19). Presented at the AIAA: Aviation Technology, Integration,
and Operations Conference, Washington, D.C., USA: AIAA. https://doi.org/10.2514/6.2016-3764'
chicago: Mikić, Gregor, Alex Stoll, Joe Bevirt, Rok Grah, and Mark Moore. “Fuselage
Boundary Layer Ingestion Propulsion Applied to a Thin Haul Commuter Aircraft for
Optimal Efficiency,” 1–19. AIAA, 2016. https://doi.org/10.2514/6.2016-3764.
ieee: 'G. Mikić, A. Stoll, J. Bevirt, R. Grah, and M. Moore, “Fuselage boundary
layer ingestion propulsion applied to a thin haul commuter aircraft for optimal
efficiency,” presented at the AIAA: Aviation Technology, Integration, and Operations
Conference, Washington, D.C., USA, 2016, pp. 1–19.'
ista: 'Mikić G, Stoll A, Bevirt J, Grah R, Moore M. 2016. Fuselage boundary layer
ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency.
AIAA: Aviation Technology, Integration, and Operations Conference, 1–19.'
mla: Mikić, Gregor, et al. Fuselage Boundary Layer Ingestion Propulsion Applied
to a Thin Haul Commuter Aircraft for Optimal Efficiency. AIAA, 2016, pp. 1–19,
doi:10.2514/6.2016-3764.
short: G. Mikić, A. Stoll, J. Bevirt, R. Grah, M. Moore, in:, AIAA, 2016, pp. 1–19.
conference:
end_date: 2016-06-17
location: Washington, D.C., USA
name: 'AIAA: Aviation Technology, Integration, and Operations Conference'
start_date: 2016-06-13
date_created: 2018-12-11T11:50:47Z
date_published: 2016-06-01T00:00:00Z
date_updated: 2023-02-21T10:17:50Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.2514/6.2016-3764
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ntrs.nasa.gov/search.jsp?R=20160010167&hterms=Fuselage+boundary+layer+ingestion+propulsion+applied+thin+haul+commuter+aircraft+optimal+efficiency&qs=N%3D0%26Ntk%3DAll%26Ntt%3DFuselage%2520boundary%2520layer%2520ingestion%2520propulsion%2520applied%2520to%2520a%2520thin%2520haul%2520commuter%2520aircraft%2520for%2520optimal%2520efficiency%26Ntx%3Dmode%2520matchallpartial%26Nm%3D123%7CCollection%7CNASA%2520STI%7C%7C17%7CCollection%7CNACA
month: '06'
oa: 1
oa_version: Preprint
page: 1 - 19
publication_status: published
publisher: AIAA
publist_id: '6114'
quality_controlled: '1'
scopus_import: 1
status: public
title: Fuselage boundary layer ingestion propulsion applied to a thin haul commuter
aircraft for optimal efficiency
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2016'
...
---
_id: '1242'
abstract:
- lang: eng
text: A crucial step in the regulation of gene expression is binding of transcription
factor (TF) proteins to regulatory sites along the DNA. But transcription factors
act at nanomolar concentrations, and noise due to random arrival of these molecules
at their binding sites can severely limit the precision of regulation. Recent
work on the optimization of information flow through regulatory networks indicates
that the lower end of the dynamic range of concentrations is simply inaccessible,
overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain
proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest
a scheme in which transcription factors also act as indirect translational regulators,
binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule
acts as an independent sensor of the input concentration, and averaging over these
multiple sensors reduces the noise. We analyze information flow through this scheme
and identify conditions under which it outperforms direct transcriptional regulation.
Our results suggest that the dual role of homeodomain proteins is not just a historical
accident, but a solution to a crucial physics problem in the regulation of gene
expression.
acknowledgement: "We thank T. Gregor, A. Prochaintz, and others for\r\nhelpful discussions.
This work was supported in part by\r\nGrants No. PHY-1305525 and No. CCF-0939370
from the\r\nUS National Science Foundation and by the W.M. Keck\r\nFoundation. A.M.W.
acknowledges the support by European\r\nResearch Council (ERC) Grant No. MCCIG PCIG10–GA-\r\n2011–303561.
G.T. and T.R.S. were supported by Austrian\r\nScience Fund (FWF) Grant No. P28844S."
article_number: '022404'
author:
- first_name: Thomas R
full_name: Sokolowski, Thomas R
id: 3E999752-F248-11E8-B48F-1D18A9856A87
last_name: Sokolowski
orcid: 0000-0002-1287-3779
- first_name: Aleksandra
full_name: Walczak, Aleksandra
last_name: Walczak
- first_name: William
full_name: Bialek, William
last_name: Bialek
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of
transcription factor action by translational regulation. Physical Review E
Statistical Nonlinear and Soft Matter Physics. 2016;93(2). doi:10.1103/PhysRevE.93.022404
apa: Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending
the dynamic range of transcription factor action by translational regulation.
Physical Review E Statistical Nonlinear and Soft Matter Physics. American
Institute of Physics. https://doi.org/10.1103/PhysRevE.93.022404
chicago: Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik.
“Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.”
Physical Review E Statistical Nonlinear and Soft Matter Physics. American
Institute of Physics, 2016. https://doi.org/10.1103/PhysRevE.93.022404.
ieee: T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic
range of transcription factor action by translational regulation,” Physical
Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2. American
Institute of Physics, 2016.
ista: Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic
range of transcription factor action by translational regulation. Physical Review
E Statistical Nonlinear and Soft Matter Physics. 93(2), 022404.
mla: Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription
Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear
and Soft Matter Physics, vol. 93, no. 2, 022404, American Institute of Physics,
2016, doi:10.1103/PhysRevE.93.022404.
short: T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E Statistical
Nonlinear and Soft Matter Physics 93 (2016).
date_created: 2018-12-11T11:50:54Z
date_published: 2016-02-04T00:00:00Z
date_updated: 2021-01-12T06:49:20Z
day: '04'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.93.022404
intvolume: ' 93'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1507.02562
month: '02'
oa: 1
oa_version: Preprint
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '6088'
quality_controlled: '1'
scopus_import: 1
status: public
title: Extending the dynamic range of transcription factor action by translational
regulation
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 93
year: '2016'
...
---
_id: '1244'
abstract:
- lang: eng
text: Cell polarity refers to a functional spatial organization of proteins that
is crucial for the control of essential cellular processes such as growth and
division. To establish polarity, cells rely on elaborate regulation networks that
control the distribution of proteins at the cell membrane. In fission yeast cells,
a microtubule-dependent network has been identified that polarizes the distribution
of signaling proteins that restricts growth to cell ends and targets the cytokinetic
machinery to the middle of the cell. Although many molecular components have been
shown to play a role in this network, it remains unknown which molecular functionalities
are minimally required to establish a polarized protein distribution in this system.
Here we show that a membrane-binding protein fragment, which distributes homogeneously
in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching
it to a cytoplasmic microtubule end-binding protein. This concentration results
in a polarized pattern of chimera proteins with a spatial extension that is very
reminiscent of natural polarity patterns in fission yeast. However, chimera levels
fluctuate in response to microtubule dynamics, and disruption of microtubules
leads to disappearance of the pattern. Numerical simulations confirm that the
combined functionality of membrane anchoring and microtubule tip affinity is in
principle sufficient to create polarized patterns. Our chimera protein may thus
represent a simple molecular functionality that is able to polarize the membrane,
onto which additional layers of molecular complexity may be built to provide the
temporal robustness that is typical of natural polarity patterns.
acknowledgement: "We thank Sophie Martin, Ken Sawin, Stephen Huisman,\r\nand Damian
Brunner for strains; Julianne\r\nTeapal, Marcel Janson, Sergio Rincon,\r\nand Phong
Tran for technical assistance; Andrew Mugler and Bela Mulder for\r\ndiscussions;
and Sander Tans, Phong Tran,\r\nand Anne Paoletti for critical reading\r\nof the
manuscript. This work is part of the research program of the\r\n“\r\nStichting\r\nvoor
Fundamenteel Onderzoek de Materie,\r\n”\r\nwhich is financially supported by\r\nthe\r\n“\r\nNederlandse
organisatie voor Wete\r\nnschappelijk Onderzoek (NWO).\r\n”"
author:
- first_name: Pierre
full_name: Recouvreux, Pierre
last_name: Recouvreux
- first_name: Thomas R
full_name: Sokolowski, Thomas R
id: 3E999752-F248-11E8-B48F-1D18A9856A87
last_name: Sokolowski
orcid: 0000-0002-1287-3779
- first_name: Aristea
full_name: Grammoustianou, Aristea
last_name: Grammoustianou
- first_name: Pieter
full_name: Tenwolde, Pieter
last_name: Tenwolde
- first_name: Marileen
full_name: Dogterom, Marileen
last_name: Dogterom
citation:
ama: Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. Chimera
proteins with affinity for membranes and microtubule tips polarize in the membrane
of fission yeast cells. PNAS. 2016;113(7):1811-1816. doi:10.1073/pnas.1419248113
apa: Recouvreux, P., Sokolowski, T. R., Grammoustianou, A., Tenwolde, P., &
Dogterom, M. (2016). Chimera proteins with affinity for membranes and microtubule
tips polarize in the membrane of fission yeast cells. PNAS. National Academy
of Sciences. https://doi.org/10.1073/pnas.1419248113
chicago: Recouvreux, Pierre, Thomas R Sokolowski, Aristea Grammoustianou, Pieter
Tenwolde, and Marileen Dogterom. “Chimera Proteins with Affinity for Membranes
and Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS.
National Academy of Sciences, 2016. https://doi.org/10.1073/pnas.1419248113.
ieee: P. Recouvreux, T. R. Sokolowski, A. Grammoustianou, P. Tenwolde, and M. Dogterom,
“Chimera proteins with affinity for membranes and microtubule tips polarize in
the membrane of fission yeast cells,” PNAS, vol. 113, no. 7. National Academy
of Sciences, pp. 1811–1816, 2016.
ista: Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. 2016.
Chimera proteins with affinity for membranes and microtubule tips polarize in
the membrane of fission yeast cells. PNAS. 113(7), 1811–1816.
mla: Recouvreux, Pierre, et al. “Chimera Proteins with Affinity for Membranes and
Microtubule Tips Polarize in the Membrane of Fission Yeast Cells.” PNAS,
vol. 113, no. 7, National Academy of Sciences, 2016, pp. 1811–16, doi:10.1073/pnas.1419248113.
short: P. Recouvreux, T.R. Sokolowski, A. Grammoustianou, P. Tenwolde, M. Dogterom,
PNAS 113 (2016) 1811–1816.
date_created: 2018-12-11T11:50:55Z
date_published: 2016-02-16T00:00:00Z
date_updated: 2021-01-12T06:49:21Z
day: '16'
department:
- _id: GaTk
doi: 10.1073/pnas.1419248113
intvolume: ' 113'
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763754/
month: '02'
oa: 1
oa_version: Submitted Version
page: 1811 - 1816
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '6085'
quality_controlled: '1'
scopus_import: 1
status: public
title: Chimera proteins with affinity for membranes and microtubule tips polarize
in the membrane of fission yeast cells
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 113
year: '2016'
...
---
_id: '1248'
abstract:
- lang: eng
text: Life depends as much on the flow of information as on the flow of energy.
Here we review the many efforts to make this intuition precise. Starting with
the building blocks of information theory, we explore examples where it has been
possible to measure, directly, the flow of information in biological networks,
or more generally where information-theoretic ideas have been used to guide the
analysis of experiments. Systems of interest range from single molecules (the
sequence diversity in families of proteins) to groups of organisms (the distribution
of velocities in flocks of birds), and all scales in between. Many of these analyses
are motivated by the idea that biological systems may have evolved to optimize
the gathering and representation of information, and we review the experimental
evidence for this optimization, again across a wide range of scales.
acknowledgement: "Our work was supported in part by the US\r\nNational Science Foundation
(PHY–1305525 and CCF–\r\n0939370), by the Austrian Science Foundation (FWF\r\nP25651),
by the Human Frontiers Science Program, and\r\nby the Simons and Swartz Foundations."
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Tkačik G, Bialek W. Information processing in living systems. Annual Review
of Condensed Matter Physics. 2016;7:89-117. doi:10.1146/annurev-conmatphys-031214-014803
apa: Tkačik, G., & Bialek, W. (2016). Information processing in living systems.
Annual Review of Condensed Matter Physics. Annual Reviews. https://doi.org/10.1146/annurev-conmatphys-031214-014803
chicago: Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.”
Annual Review of Condensed Matter Physics. Annual Reviews, 2016. https://doi.org/10.1146/annurev-conmatphys-031214-014803.
ieee: G. Tkačik and W. Bialek, “Information processing in living systems,” Annual
Review of Condensed Matter Physics, vol. 7. Annual Reviews, pp. 89–117, 2016.
ista: Tkačik G, Bialek W. 2016. Information processing in living systems. Annual
Review of Condensed Matter Physics. 7, 89–117.
mla: Tkačik, Gašper, and William Bialek. “Information Processing in Living Systems.”
Annual Review of Condensed Matter Physics, vol. 7, Annual Reviews, 2016,
pp. 89–117, doi:10.1146/annurev-conmatphys-031214-014803.
short: G. Tkačik, W. Bialek, Annual Review of Condensed Matter Physics 7 (2016)
89–117.
date_created: 2018-12-11T11:50:56Z
date_published: 2016-03-10T00:00:00Z
date_updated: 2021-01-12T06:49:23Z
day: '10'
department:
- _id: GaTk
doi: 10.1146/annurev-conmatphys-031214-014803
intvolume: ' 7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1412.8752
month: '03'
oa: 1
oa_version: Preprint
page: 89 - 117
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: Annual Review of Condensed Matter Physics
publication_status: published
publisher: Annual Reviews
publist_id: '6080'
quality_controlled: '1'
scopus_import: 1
status: public
title: Information processing in living systems
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2016'
...
---
_id: '1260'
abstract:
- lang: eng
text: In this work, the Gardner problem of inferring interactions and fields for
an Ising neural network from given patterns under a local stability hypothesis
is addressed under a dual perspective. By means of duality arguments, an integer
linear system is defined whose solution space is the dual of the Gardner space
and whose solutions represent mutually unstable patterns. We propose and discuss
Monte Carlo methods in order to find and remove unstable patterns and uniformly
sample the space of interactions thereafter. We illustrate the problem on a set
of real data and perform ensemble calculation that shows how the emergence of
phase dominated by unstable patterns can be triggered in a nonlinear discontinuous
way.
article_number: '1650067'
article_processing_charge: No
article_type: original
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: De Martino D. The dual of the space of interactions in neural network models.
International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674
apa: De Martino, D. (2016). The dual of the space of interactions in neural network
models. International Journal of Modern Physics C. World Scientific Publishing.
https://doi.org/10.1142/S0129183116500674
chicago: De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network
Models.” International Journal of Modern Physics C. World Scientific Publishing,
2016. https://doi.org/10.1142/S0129183116500674.
ieee: D. De Martino, “The dual of the space of interactions in neural network models,”
International Journal of Modern Physics C, vol. 27, no. 6. World Scientific
Publishing, 2016.
ista: De Martino D. 2016. The dual of the space of interactions in neural network
models. International Journal of Modern Physics C. 27(6), 1650067.
mla: De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network
Models.” International Journal of Modern Physics C, vol. 27, no. 6, 1650067,
World Scientific Publishing, 2016, doi:10.1142/S0129183116500674.
short: D. De Martino, International Journal of Modern Physics C 27 (2016).
date_created: 2018-12-11T11:51:00Z
date_published: 2016-06-01T00:00:00Z
date_updated: 2021-01-12T06:49:28Z
day: '01'
department:
- _id: GaTk
doi: 10.1142/S0129183116500674
external_id:
arxiv:
- '1505.02963'
intvolume: ' 27'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1505.02963
month: '06'
oa: 1
oa_version: Preprint
publication: International Journal of Modern Physics C
publication_status: published
publisher: World Scientific Publishing
publist_id: '6065'
quality_controlled: '1'
scopus_import: 1
status: public
title: The dual of the space of interactions in neural network models
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 27
year: '2016'
...
---
_id: '1266'
abstract:
- lang: eng
text: 'Cortical networks exhibit ‘global oscillations’, in which neural spike times
are entrained to an underlying oscillatory rhythm, but where individual neurons
fire irregularly, on only a fraction of cycles. While the network dynamics underlying
global oscillations have been well characterised, their function is debated. Here,
we show that such global oscillations are a direct consequence of optimal efficient
coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary
spikes, neurons need to share information about the network state. Ideally, membrane
potentials should be strongly correlated and reflect a ‘prediction error’ while
the spikes themselves are uncorrelated and occur rarely. We show that the most
efficient representation is when: (i) spike times are entrained to a global Gamma
rhythm (implying a consistent representation of the error); but (ii) few neurons
fire on each cycle (implying high efficiency), while (iii) excitation and inhibition
are tightly balanced. This suggests that cortical networks exhibiting such dynamics
are tuned to achieve a maximally efficient population code.'
acknowledgement: Boris Gutkin acknowledges funding by the Russian Academic Excellence
Project '5-100’.
article_number: e13824
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Boris
full_name: Gutkin, Boris
last_name: Gutkin
- first_name: Sophie
full_name: Denève, Sophie
last_name: Denève
citation:
ama: Chalk MJ, Gutkin B, Denève S. Neural oscillations as a signature of efficient
coding in the presence of synaptic delays. eLife. 2016;5(2016JULY). doi:10.7554/eLife.13824
apa: Chalk, M. J., Gutkin, B., & Denève, S. (2016). Neural oscillations as a
signature of efficient coding in the presence of synaptic delays. ELife.
eLife Sciences Publications. https://doi.org/10.7554/eLife.13824
chicago: Chalk, Matthew J, Boris Gutkin, and Sophie Denève. “Neural Oscillations
as a Signature of Efficient Coding in the Presence of Synaptic Delays.” ELife.
eLife Sciences Publications, 2016. https://doi.org/10.7554/eLife.13824.
ieee: M. J. Chalk, B. Gutkin, and S. Denève, “Neural oscillations as a signature
of efficient coding in the presence of synaptic delays,” eLife, vol. 5,
no. 2016JULY. eLife Sciences Publications, 2016.
ista: Chalk MJ, Gutkin B, Denève S. 2016. Neural oscillations as a signature of
efficient coding in the presence of synaptic delays. eLife. 5(2016JULY), e13824.
mla: Chalk, Matthew J., et al. “Neural Oscillations as a Signature of Efficient
Coding in the Presence of Synaptic Delays.” ELife, vol. 5, no. 2016JULY,
e13824, eLife Sciences Publications, 2016, doi:10.7554/eLife.13824.
short: M.J. Chalk, B. Gutkin, S. Denève, ELife 5 (2016).
date_created: 2018-12-11T11:51:02Z
date_published: 2016-07-01T00:00:00Z
date_updated: 2021-01-12T06:49:30Z
day: '01'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.7554/eLife.13824
file:
- access_level: open_access
checksum: dc52d967dc76174477bb258d84be2899
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:20Z
date_updated: 2020-07-14T12:44:42Z
file_id: '4874'
file_name: IST-2016-700-v1+1_e13824-download.pdf
file_size: 2819055
relation: main_file
file_date_updated: 2020-07-14T12:44:42Z
has_accepted_license: '1'
intvolume: ' 5'
issue: 2016JULY
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
publication: eLife
publication_status: published
publisher: eLife Sciences Publications
publist_id: '6056'
pubrep_id: '700'
quality_controlled: '1'
scopus_import: 1
status: public
title: Neural oscillations as a signature of efficient coding in the presence of synaptic
delays
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 5
year: '2016'
...
---
_id: '1290'
abstract:
- lang: eng
text: We developed a competition-based screening strategy to identify compounds
that invert the selective advantage of antibiotic resistance. Using our assay,
we screened over 19,000 compounds for the ability to select against the TetA tetracycline-resistance
efflux pump in Escherichia coli and identified two hits, β-thujaplicin and disulfiram.
Treating a tetracycline-resistant population with β-thujaplicin selects for loss
of the resistance gene, enabling an effective second-phase treatment with doxycycline.
acknowledgement: "This work was supported in part by National Institute of Allergy
and Infectious Diseases grant U54 AI057159, US National Institutes of Health grants
R01 GM081617 (to R.K.) and GM086258 (to J.C.), European Research Council FP7 ERC
grant 281891 (to R.K.) and a National Science Foundation Graduate Fellowship (to
L.K.S.).\r\n"
author:
- first_name: Laura
full_name: Stone, Laura
last_name: Stone
- first_name: Michael
full_name: Baym, Michael
last_name: Baym
- first_name: Tami
full_name: Lieberman, Tami
last_name: Lieberman
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Jon
full_name: Clardy, Jon
last_name: Clardy
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. Compounds that
select against the tetracycline-resistance efflux pump. Nature Chemical Biology.
2016;12(11):902-904. doi:10.1038/nchembio.2176
apa: Stone, L., Baym, M., Lieberman, T., Chait, R. P., Clardy, J., & Kishony,
R. (2016). Compounds that select against the tetracycline-resistance efflux pump.
Nature Chemical Biology. Nature Publishing Group. https://doi.org/10.1038/nchembio.2176
chicago: Stone, Laura, Michael Baym, Tami Lieberman, Remy P Chait, Jon Clardy, and
Roy Kishony. “Compounds That Select against the Tetracycline-Resistance Efflux
Pump.” Nature Chemical Biology. Nature Publishing Group, 2016. https://doi.org/10.1038/nchembio.2176.
ieee: L. Stone, M. Baym, T. Lieberman, R. P. Chait, J. Clardy, and R. Kishony, “Compounds
that select against the tetracycline-resistance efflux pump,” Nature Chemical
Biology, vol. 12, no. 11. Nature Publishing Group, pp. 902–904, 2016.
ista: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. 2016. Compounds
that select against the tetracycline-resistance efflux pump. Nature Chemical Biology.
12(11), 902–904.
mla: Stone, Laura, et al. “Compounds That Select against the Tetracycline-Resistance
Efflux Pump.” Nature Chemical Biology, vol. 12, no. 11, Nature Publishing
Group, 2016, pp. 902–04, doi:10.1038/nchembio.2176.
short: L. Stone, M. Baym, T. Lieberman, R.P. Chait, J. Clardy, R. Kishony, Nature
Chemical Biology 12 (2016) 902–904.
date_created: 2018-12-11T11:51:10Z
date_published: 2016-11-01T00:00:00Z
date_updated: 2021-01-12T06:49:39Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/nchembio.2176
intvolume: ' 12'
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069154/
month: '11'
oa: 1
oa_version: Preprint
page: 902 - 904
publication: Nature Chemical Biology
publication_status: published
publisher: Nature Publishing Group
publist_id: '6026'
quality_controlled: '1'
scopus_import: 1
status: public
title: Compounds that select against the tetracycline-resistance efflux pump
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2016'
...
---
_id: '1320'
abstract:
- lang: eng
text: 'In recent years, several biomolecular systems have been shown to be scale-invariant
(SI), i.e. to show the same output dynamics when exposed to geometrically scaled
input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant
inputs. In this article, we show that SI systems-as well as systems invariant
with respect to other input transformations-can realize nonlinear differential
operators: when excited by inputs obeying functional forms characteristic for
a given class of invariant systems, the systems'' outputs converge to constant
values directly quantifying the speed of the input.'
acknowledgement: The research leading to these results has received funding from the
People Programme (Marie Curie Actions) of the European Union's Seventh Framework
Programme (FP7/2007-2013) under REA grant agreement n° [291734]. Work supported
in part by grants AFOSR FA9550-14-1-0060 and NIH 1R01GM100473.
article_number: '7526722'
author:
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Eduardo
full_name: Sontag, Eduardo
last_name: Sontag
citation:
ama: 'Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators.
In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722'
apa: 'Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear
differential operators (Vol. 2016–July). Presented at the ACC: American Control
Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722'
chicago: Lang, Moritz, and Eduardo Sontag. “Scale-Invariant Systems Realize Nonlinear
Differential Operators,” Vol. 2016–July. IEEE, 2016. https://doi.org/10.1109/ACC.2016.7526722.
ieee: 'M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential
operators,” presented at the ACC: American Control Conference, Boston, MA, USA,
2016, vol. 2016–July.'
ista: 'Lang M, Sontag E. 2016. Scale-invariant systems realize nonlinear differential
operators. ACC: American Control Conference vol. 2016–July, 7526722.'
mla: Lang, Moritz, and Eduardo Sontag. Scale-Invariant Systems Realize Nonlinear
Differential Operators. Vol. 2016–July, 7526722, IEEE, 2016, doi:10.1109/ACC.2016.7526722.
short: M. Lang, E. Sontag, in:, IEEE, 2016.
conference:
end_date: 2016-07-08
location: Boston, MA, USA
name: 'ACC: American Control Conference'
start_date: 2016-07-06
date_created: 2018-12-11T11:51:21Z
date_published: 2016-07-28T00:00:00Z
date_updated: 2021-01-12T06:49:51Z
day: '28'
ddc:
- '003'
- '621'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1109/ACC.2016.7526722
ec_funded: 1
file:
- access_level: local
checksum: 7219432b43defc62a0d45f48d4ce6a19
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:17Z
date_updated: 2020-07-14T12:44:43Z
file_id: '5203'
file_name: IST-2017-810-v1+1_root.pdf
file_size: 539166
relation: main_file
file_date_updated: 2020-07-14T12:44:43Z
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication_status: published
publisher: IEEE
publist_id: '5950'
pubrep_id: '810'
quality_controlled: '1'
scopus_import: 1
status: public
title: Scale-invariant systems realize nonlinear differential operators
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 2016-July
year: '2016'
...
---
_id: '1332'
abstract:
- lang: eng
text: Antibiotic-sensitive and -resistant bacteria coexist in natural environments
with low, if detectable, antibiotic concentrations. Except possibly around localized
antibiotic sources, where resistance can provide a strong advantage, bacterial
fitness is dominated by stresses unaffected by resistance to the antibiotic. How
do such mixed and heterogeneous conditions influence the selective advantage or
disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels
of tetracyclines potentiate selection for or against tetracycline resistance around
localized sources of almost any toxin or stress. Furthermore, certain stresses
generate alternating rings of selection for and against resistance around a localized
source of the antibiotic. In these conditions, localized antibiotic sources, even
at high strengths, can actually produce a net selection against resistance to
the antibiotic. Our results show that interactions between the effects of an antibiotic
and other stresses in inhomogeneous environments can generate pervasive, complex
patterns of selection both for and against antibiotic resistance.
acknowledgement: This work was partially supported by US National Institutes of Health
grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant
No. 152/11, and the European Research Council FP7 ERC Grant 281891.
article_number: '10333'
author:
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Adam
full_name: Palmer, Adam
last_name: Palmer
- first_name: Idan
full_name: Yelin, Idan
last_name: Yelin
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against
antibiotic resistance in inhomogeneous multistress environments. Nature Communications.
2016;7. doi:10.1038/ncomms10333
apa: Chait, R. P., Palmer, A., Yelin, I., & Kishony, R. (2016). Pervasive selection
for and against antibiotic resistance in inhomogeneous multistress environments.
Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms10333
chicago: Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection
for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.”
Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms10333.
ieee: R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for
and against antibiotic resistance in inhomogeneous multistress environments,”
Nature Communications, vol. 7. Nature Publishing Group, 2016.
ista: Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and
against antibiotic resistance in inhomogeneous multistress environments. Nature
Communications. 7, 10333.
mla: Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance
in Inhomogeneous Multistress Environments.” Nature Communications, vol.
7, 10333, Nature Publishing Group, 2016, doi:10.1038/ncomms10333.
short: R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016).
date_created: 2018-12-11T11:51:25Z
date_published: 2016-01-20T00:00:00Z
date_updated: 2021-01-12T06:49:57Z
day: '20'
ddc:
- '570'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/ncomms10333
file:
- access_level: open_access
checksum: ef147bcbb8bd37e9079cf3ce06f5815d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:52Z
date_updated: 2020-07-14T12:44:44Z
file_id: '5039'
file_name: IST-2016-662-v1+1_ncomms10333.pdf
file_size: 1844107
relation: main_file
file_date_updated: 2020-07-14T12:44:44Z
has_accepted_license: '1'
intvolume: ' 7'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Nature Communications
publication_status: published
publisher: Nature Publishing Group
publist_id: '5936'
pubrep_id: '662'
quality_controlled: '1'
scopus_import: 1
status: public
title: Pervasive selection for and against antibiotic resistance in inhomogeneous
multistress environments
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2016'
...
---
_id: '1342'
abstract:
- lang: eng
text: A key aspect of bacterial survival is the ability to evolve while migrating
across spatially varying environmental challenges. Laboratory experiments, however,
often study evolution in well-mixed systems. Here, we introduce an experimental
device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria
spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that
allowed visual observation of mutation and selection in a migrating bacterial
front.While resistance increased consistently, multiple coexisting lineages diversified
both phenotypically and genotypically. Analyzing mutants at and behind the propagating
front,we found that evolution is not always led by the most resistant mutants;
highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate
provides a versatile platformfor studying microbial adaption and directly visualizing
evolutionary dynamics.
author:
- first_name: Michael
full_name: Baym, Michael
last_name: Baym
- first_name: Tami
full_name: Lieberman, Tami
last_name: Lieberman
- first_name: Eric
full_name: Kelsic, Eric
last_name: Kelsic
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Rotem
full_name: Gross, Rotem
last_name: Gross
- first_name: Idan
full_name: Yelin, Idan
last_name: Yelin
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on
antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822
apa: Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., &
Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes.
Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aag0822
chicago: Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross,
Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic
Landscapes.” Science. American Association for the Advancement of Science,
2016. https://doi.org/10.1126/science.aag0822.
ieee: M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,”
Science, vol. 353, no. 6304. American Association for the Advancement of
Science, pp. 1147–1151, 2016.
ista: Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016.
Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304),
1147–1151.
mla: Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.”
Science, vol. 353, no. 6304, American Association for the Advancement of
Science, 2016, pp. 1147–51, doi:10.1126/science.aag0822.
short: M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony,
Science 353 (2016) 1147–1151.
date_created: 2018-12-11T11:51:29Z
date_published: 2016-09-09T00:00:00Z
date_updated: 2021-01-12T06:50:01Z
day: '09'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.aag0822
intvolume: ' 353'
issue: '6304'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/
month: '09'
oa: 1
oa_version: Preprint
page: 1147 - 1151
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '5911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Spatiotemporal microbial evolution on antibiotic landscapes
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 353
year: '2016'
...
---
_id: '1394'
abstract:
- lang: eng
text: "The solution space of genome-scale models of cellular metabolism provides
a map between physically\r\nviable flux configurations and cellular metabolic
phenotypes described, at the most basic level, by the\r\ncorresponding growth
rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat
empirical growth rate distributions recently obtained in experiments at single-cell
resolution can\r\nbe explained in terms of a trade-off between the higher fitness
of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based
on this, we propose a minimal model for the evolution of\r\na large bacterial
population that captures this trade-off. The scaling relationships observed in\r\nexperiments
encode, in such frameworks, for the same distance from the maximum achievable
growth\r\nrate, the same degree of growth rate maximization, and/or the same rate
of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions,
these results allow for multiple\r\nimplications and extensions in spite of the
underlying conceptual simplicity."
acknowledgement: "The research leading to these results has received funding from
the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038."
article_number: '036005'
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Fabrizio
full_name: Capuani, Fabrizio
last_name: Capuani
- first_name: Andrea
full_name: De Martino, Andrea
last_name: De Martino
citation:
ama: 'De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial
metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005'
apa: 'De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy
in bacterial metabolism: the phenotypic trade-off behind empirical growth rate
distributions in E. coli. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005'
chicago: 'De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth
against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical
Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing
Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.'
ieee: 'D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in
bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing Ltd., 2016.'
ista: 'De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial
metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli. Physical Biology. 13(3), 036005.'
mla: 'De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism:
The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.”
Physical Biology, vol. 13, no. 3, 036005, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/3/036005.'
short: D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016).
date_created: 2018-12-11T11:51:46Z
date_published: 2016-05-27T00:00:00Z
date_updated: 2021-01-12T06:50:23Z
day: '27'
department:
- _id: GaTk
doi: 10.1088/1478-3975/13/3/036005
ec_funded: 1
intvolume: ' 13'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1601.03243
month: '05'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Biology
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '5815'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Growth against entropy in bacterial metabolism: the phenotypic trade-off behind
empirical growth rate distributions in E. coli'
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2016'
...
---
_id: '1420'
abstract:
- lang: eng
text: 'Selection, mutation, and random drift affect the dynamics of allele frequencies
and consequently of quantitative traits. While the macroscopic dynamics of quantitative
traits can be measured, the underlying allele frequencies are typically unobserved.
Can we understand how the macroscopic observables evolve without following these
microscopic processes? This problem has been studied previously by analogy with
statistical mechanics: the allele frequency distribution at each time point is
approximated by the stationary form, which maximizes entropy. We explore the limitations
of this method when mutation is small (4Nμ < 1) so that populations are typically
close to fixation, and we extend the theory in this regime to account for changes
in mutation strength. We consider a single diallelic locus either under directional
selection or with overdominance and then generalize to multiple unlinked biallelic
loci with unequal effects. We find that the maximum-entropy approximation is remarkably
accurate, even when mutation and selection change rapidly. '
article_processing_charge: No
author:
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of
quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127
apa: Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation
for the dynamics of quantitative traits. Genetics. Genetics Society of
America. https://doi.org/10.1534/genetics.115.184127
chicago: Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation
for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of
America, 2016. https://doi.org/10.1534/genetics.115.184127.
ieee: K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics
of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of
America, pp. 1523–1548, 2016.
ista: Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics
of quantitative traits. Genetics. 202(4), 1523–1548.
mla: Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative
Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016,
pp. 1523–48, doi:10.1534/genetics.115.184127.
short: K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548.
date_created: 2018-12-11T11:51:55Z
date_published: 2016-04-06T00:00:00Z
date_updated: 2022-08-01T10:49:55Z
day: '06'
department:
- _id: GaTk
- _id: NiBa
doi: 10.1534/genetics.115.184127
ec_funded: 1
external_id:
arxiv:
- '1510.08344'
intvolume: ' 202'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1510.08344
month: '04'
oa: 1
oa_version: Preprint
page: 1523 - 1548
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
publication: Genetics
publication_status: published
publisher: Genetics Society of America
publist_id: '5787'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A general approximation for the dynamics of quantitative traits
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2016'
...
---
_id: '1485'
abstract:
- lang: eng
text: In this article the notion of metabolic turnover is revisited in the light
of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo
methods we perform an exact sampling of the enzymatic fluxes in a genome scale
metabolic network of E. Coli in stationary growth conditions from which we infer
the metabolites turnover times. However the latter are inferred from net fluxes,
and we argue that this approximation is not valid for enzymes working nearby thermodynamic
equilibrium. We recalculate turnover times from total fluxes by performing an
energy balance analysis of the network and recurring to the fluctuation theorem.
We find in many cases values one of order of magnitude lower, implying a faster
picture of intermediate metabolism.
article_number: '016003'
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from
the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003
apa: De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E.
Coli from the energy balance analysis. Physical Biology. IOP Publishing
Ltd. https://doi.org/10.1088/1478-3975/13/1/016003
chicago: De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of
E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing
Ltd., 2016. https://doi.org/10.1088/1478-3975/13/1/016003.
ieee: D. De Martino, “Genome-scale estimate of the metabolic turnover of E. Coli
from the energy balance analysis,” Physical Biology, vol. 13, no. 1. IOP
Publishing Ltd., 2016.
ista: De Martino D. 2016. Genome-scale estimate of the metabolic turnover of E.
Coli from the energy balance analysis. Physical Biology. 13(1), 016003.
mla: De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E.
Coli from the Energy Balance Analysis.” Physical Biology, vol. 13, no.
1, 016003, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/1/016003.
short: D. De Martino, Physical Biology 13 (2016).
date_created: 2018-12-11T11:52:18Z
date_published: 2016-01-29T00:00:00Z
date_updated: 2021-01-12T06:51:04Z
day: '29'
department:
- _id: GaTk
doi: 10.1088/1478-3975/13/1/016003
ec_funded: 1
intvolume: ' 13'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1505.04613
month: '01'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Biology
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '5702'
quality_controlled: '1'
scopus_import: 1
status: public
title: Genome-scale estimate of the metabolic turnover of E. Coli from the energy
balance analysis
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2016'
...
---
_id: '1148'
abstract:
- lang: eng
text: Continuous-time Markov chain (CTMC) models have become a central tool for
understanding the dynamics of complex reaction networks and the importance of
stochasticity in the underlying biochemical processes. When such models are employed
to answer questions in applications, in order to ensure that the model provides
a sufficiently accurate representation of the real system, it is of vital importance
that the model parameters are inferred from real measured data. This, however,
is often a formidable task and all of the existing methods fail in one case or
the other, usually because the underlying CTMC model is high-dimensional and computationally
difficult to analyze. The parameter inference methods that tend to scale best
in the dimension of the CTMC are based on so-called moment closure approximations.
However, there exists a large number of different moment closure approximations
and it is typically hard to say a priori which of the approximations is the most
suitable for the inference procedure. Here, we propose a moment-based parameter
inference method that automatically chooses the most appropriate moment closure
method. Accordingly, contrary to existing methods, the user is not required to
be experienced in moment closure techniques. In addition to that, our method adaptively
changes the approximation during the parameter inference to ensure that always
the best approximation is used, even in cases where different approximations are
best in different regions of the parameter space. © 2016 Elsevier Ireland Ltd
acknowledgement: This work is based on the CMSB 2015 paper “Adaptive moment closure
for parameter inference of biochemical reaction networks” (Bogomolov et al., 2015).
The work was partly supported by the German Research Foundation (DFG) as part of
the Transregional Collaborative Research Center “Automatic Verification and Analysis
of Complex Systems” (SFB/TR 14 AVACS1), by the European Research Council (ERC) under
grant 267989 (QUAREM) and by the Austrian Science Fund (FWF) under grants S11402-N23
(RiSE) and Z211-N23 (Wittgenstein Award). J.R. acknowledges support from the People
Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme
(FP7/2007-2013) under REA grant agreement no. 291734.
author:
- first_name: Christian
full_name: Schilling, Christian
last_name: Schilling
- first_name: Sergiy
full_name: Bogomolov, Sergiy
id: 369D9A44-F248-11E8-B48F-1D18A9856A87
last_name: Bogomolov
orcid: 0000-0002-0686-0365
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000−0002−2985−7724
- first_name: Andreas
full_name: Podelski, Andreas
last_name: Podelski
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
citation:
ama: Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. Adaptive moment
closure for parameter inference of biochemical reaction networks. Biosystems.
2016;149:15-25. doi:10.1016/j.biosystems.2016.07.005
apa: Schilling, C., Bogomolov, S., Henzinger, T. A., Podelski, A., & Ruess,
J. (2016). Adaptive moment closure for parameter inference of biochemical reaction
networks. Biosystems. Elsevier. https://doi.org/10.1016/j.biosystems.2016.07.005
chicago: Schilling, Christian, Sergiy Bogomolov, Thomas A Henzinger, Andreas Podelski,
and Jakob Ruess. “Adaptive Moment Closure for Parameter Inference of Biochemical
Reaction Networks.” Biosystems. Elsevier, 2016. https://doi.org/10.1016/j.biosystems.2016.07.005.
ieee: C. Schilling, S. Bogomolov, T. A. Henzinger, A. Podelski, and J. Ruess, “Adaptive
moment closure for parameter inference of biochemical reaction networks,” Biosystems,
vol. 149. Elsevier, pp. 15–25, 2016.
ista: Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. 2016. Adaptive
moment closure for parameter inference of biochemical reaction networks. Biosystems.
149, 15–25.
mla: Schilling, Christian, et al. “Adaptive Moment Closure for Parameter Inference
of Biochemical Reaction Networks.” Biosystems, vol. 149, Elsevier, 2016,
pp. 15–25, doi:10.1016/j.biosystems.2016.07.005.
short: C. Schilling, S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, Biosystems
149 (2016) 15–25.
date_created: 2018-12-11T11:50:24Z
date_published: 2016-11-01T00:00:00Z
date_updated: 2023-02-23T10:08:46Z
day: '01'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1016/j.biosystems.2016.07.005
ec_funded: 1
intvolume: ' 149'
language:
- iso: eng
month: '11'
oa_version: None
page: 15 - 25
project:
- _id: 25EE3708-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '267989'
name: Quantitative Reactive Modeling
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Biosystems
publication_status: published
publisher: Elsevier
publist_id: '6210'
quality_controlled: '1'
related_material:
record:
- id: '1658'
relation: earlier_version
status: public
scopus_import: 1
status: public
title: Adaptive moment closure for parameter inference of biochemical reaction networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 149
year: '2016'
...
---
_id: '8094'
abstract:
- lang: eng
text: 'With the accelerated development of robot technologies, optimal control becomes
one of the central themes of research. In traditional approaches, the controller,
by its internal functionality, finds appropriate actions on the basis of the history
of sensor values, guided by the goals, intentions, objectives, learning schemes,
and so forth. The idea is that the controller controls the world---the body plus
its environment---as reliably as possible. This paper focuses on new lines of
self-organization for developmental robotics. We apply the recently developed
differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder
system from the Myorobotics toolkit. In the experiments, we observe a vast variety
of self-organized behavior patterns: when left alone, the arm realizes pseudo-random
sequences of different poses. By applying physical forces, the system can be entrained
into definite motion patterns like wiping a table. Most interestingly, after attaching
an object, the controller gets in a functional resonance with the object''s internal
dynamics, starting to shake spontaneously bottles half-filled with water or sensitively
driving an attached pendulum into a circular mode. When attached to the crank
of a wheel the neural system independently discovers how to rotate it. In this
way, the robot discovers affordances of objects its body is interacting with.'
article_processing_charge: No
author:
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
- first_name: Rafael
full_name: Hostettler, Rafael
last_name: Hostettler
- first_name: Alois
full_name: Knoll, Alois
last_name: Knoll
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
citation:
ama: 'Martius GS, Hostettler R, Knoll A, Der R. Self-organized control of an tendon
driven arm by differential extrinsic plasticity. In: Proceedings of the Artificial
Life Conference 2016. Vol 28. MIT Press; 2016:142-143. doi:10.7551/978-0-262-33936-0-ch029'
apa: 'Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized
control of an tendon driven arm by differential extrinsic plasticity. In Proceedings
of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico:
MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029'
chicago: Martius, Georg S, Rafael Hostettler, Alois Knoll, and Ralf Der. “Self-Organized
Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.” In Proceedings
of the Artificial Life Conference 2016, 28:142–43. MIT Press, 2016. https://doi.org/10.7551/978-0-262-33936-0-ch029.
ieee: G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Self-organized control
of an tendon driven arm by differential extrinsic plasticity,” in Proceedings
of the Artificial Life Conference 2016, Cancun, Mexico, 2016, vol. 28, pp.
142–143.
ista: 'Martius GS, Hostettler R, Knoll A, Der R. 2016. Self-organized control of
an tendon driven arm by differential extrinsic plasticity. Proceedings of the
Artificial Life Conference 2016. ALIFE 2016: 15th International Conference on
the Synthesis and Simulation of Living Systems vol. 28, 142–143.'
mla: Martius, Georg S., et al. “Self-Organized Control of an Tendon Driven Arm by
Differential Extrinsic Plasticity.” Proceedings of the Artificial Life Conference
2016, vol. 28, MIT Press, 2016, pp. 142–43, doi:10.7551/978-0-262-33936-0-ch029.
short: G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, Proceedings of the Artificial
Life Conference 2016, MIT Press, 2016, pp. 142–143.
conference:
end_date: 2016-07-08
location: Cancun, Mexico
name: 'ALIFE 2016: 15th International Conference on the Synthesis and Simulation
of Living Systems'
start_date: 2016-07-04
date_created: 2020-07-05T22:00:47Z
date_published: 2016-09-01T00:00:00Z
date_updated: 2021-01-12T08:16:53Z
day: '01'
ddc:
- '610'
department:
- _id: ChLa
- _id: GaTk
doi: 10.7551/978-0-262-33936-0-ch029
ec_funded: 1
file:
- access_level: open_access
checksum: cff63e7a4b8ac466ba51a9c84153a940
content_type: application/pdf
creator: cziletti
date_created: 2020-07-06T12:59:09Z
date_updated: 2020-07-14T12:48:09Z
file_id: '8096'
file_name: 2016_ProcALIFE_Martius.pdf
file_size: 678670
relation: main_file
file_date_updated: 2020-07-14T12:48:09Z
has_accepted_license: '1'
intvolume: ' 28'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 142-143
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Proceedings of the Artificial Life Conference 2016
publication_identifier:
isbn:
- '9780262339360'
publication_status: published
publisher: MIT Press
quality_controlled: '1'
scopus_import: 1
status: public
title: Self-organized control of an tendon driven arm by differential extrinsic plasticity
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: D865714E-FA4E-11E9-B85B-F5C5E5697425
volume: 28
year: '2016'
...
---
_id: '1197'
abstract:
- lang: eng
text: Across the nervous system, certain population spiking patterns are observed
far more frequently than others. A hypothesis about this structure is that these
collective activity patterns function as population codewords–collective modes–carrying
information distinct from that of any single cell. We investigate this phenomenon
in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop
a novel statistical model that decomposes the population response into modes;
it predicts the distribution of spiking activity in the ganglion cell population
with high accuracy. We found that the modes represent localized features of the
visual stimulus that are distinct from the features represented by single neurons.
Modes form clusters of activity states that are readily discriminated from one
another. When we repeated the same visual stimulus, we found that the same mode
was robustly elicited. These results suggest that retinal ganglion cells’ collective
signaling is endowed with a form of error-correcting code–a principle that may
hold in brain areas beyond retina.
acknowledgement: JSP was supported by a C.V. Starr Fellowship from the Starr Foundation
(http://www.starrfoundation.org/). GT was supported by Austrian Research Foundation
(https://www.fwf.ac.at/en/) grant FWF P25651. MJB received support from National
Eye Institute (https://nei.nih.gov/) grant EY 14196 and from the National Science
Foundation grant 1504977. The authors thank Cristina Savin and Vicent Botella-Soler
for helpful comments on the manuscript.
article_number: e1005855
author:
- first_name: Jason
full_name: Prentice, Jason
last_name: Prentice
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Mark
full_name: Ioffe, Mark
last_name: Ioffe
- first_name: Adrianna
full_name: Loback, Adrianna
last_name: Loback
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
citation:
ama: Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Error-robust modes
of the retinal population code. PLoS Computational Biology. 2016;12(11).
doi:10.1371/journal.pcbi.1005148
apa: Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M.
(2016). Error-robust modes of the retinal population code. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005148
chicago: Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik,
and Michael Berry. “Error-Robust Modes of the Retinal Population Code.” PLoS
Computational Biology. Public Library of Science, 2016. https://doi.org/10.1371/journal.pcbi.1005148.
ieee: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Error-robust
modes of the retinal population code,” PLoS Computational Biology, vol.
12, no. 11. Public Library of Science, 2016.
ista: Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2016. Error-robust
modes of the retinal population code. PLoS Computational Biology. 12(11), e1005855.
mla: Prentice, Jason, et al. “Error-Robust Modes of the Retinal Population Code.”
PLoS Computational Biology, vol. 12, no. 11, e1005855, Public Library of
Science, 2016, doi:10.1371/journal.pcbi.1005148.
short: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, PLoS Computational
Biology 12 (2016).
date_created: 2018-12-11T11:50:40Z
date_published: 2016-11-17T00:00:00Z
date_updated: 2023-02-23T14:05:40Z
day: '17'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005148
file:
- access_level: open_access
checksum: 47b08cbd4dbf32b25ba161f5f4b262cc
content_type: application/pdf
creator: kschuh
date_created: 2019-01-25T10:35:00Z
date_updated: 2020-07-14T12:44:38Z
file_id: '5884'
file_name: 2016_PLOS_Prentice.pdf
file_size: 4492021
relation: main_file
file_date_updated: 2020-07-14T12:44:38Z
has_accepted_license: '1'
intvolume: ' 12'
issue: '11'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '6153'
quality_controlled: '1'
related_material:
record:
- id: '9709'
relation: research_data
status: public
scopus_import: 1
status: public
title: Error-robust modes of the retinal population code
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2016'
...
---
_id: '948'
abstract:
- lang: eng
text: Experience constantly shapes neural circuits through a variety of plasticity
mechanisms. While the functional roles of some plasticity mechanisms are well-understood,
it remains unclear how changes in neural excitability contribute to learning.
Here, we develop a normative interpretation of intrinsic plasticity (IP) as a
key component of unsupervised learning. We introduce a novel generative mixture
model that accounts for the class-specific statistics of stimulus intensities,
and we derive a neural circuit that learns the input classes and their intensities.
We will analytically show that inference and learning for our generative model
can be achieved by a neural circuit with intensity-sensitive neurons equipped
with a specific form of IP. Numerical experiments verify our analytical derivations
and show robust behavior for artificial and natural stimuli. Our results link
IP to non-trivial input statistics, in particular the statistics of stimulus intensities
for classes to which a neuron is sensitive. More generally, our work paves the
way toward new classification algorithms that are robust to intensity variations.
acknowledgement: DFG Cluster of Excellence EXC 1077/1 (Hearing4all) and LU 1196/5-1
(JL and TM), People Programme (Marie Curie Actions) FP7/2007-2013 grant agreement
no. 291734 (CS)
alternative_title:
- Advances in Neural Information Processing Systems
author:
- first_name: Travis
full_name: Monk, Travis
last_name: Monk
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Jörg
full_name: Lücke, Jörg
last_name: Lücke
citation:
ama: 'Monk T, Savin C, Lücke J. Neurons equipped with intrinsic plasticity learn
stimulus intensity statistics. In: Vol 29. Neural Information Processing Systems;
2016:4285-4293.'
apa: 'Monk, T., Savin, C., & Lücke, J. (2016). Neurons equipped with intrinsic
plasticity learn stimulus intensity statistics (Vol. 29, pp. 4285–4293). Presented
at the NIPS: Neural Information Processing Systems, Barcelona, Spaine: Neural
Information Processing Systems.'
chicago: Monk, Travis, Cristina Savin, and Jörg Lücke. “Neurons Equipped with Intrinsic
Plasticity Learn Stimulus Intensity Statistics,” 29:4285–93. Neural Information
Processing Systems, 2016.
ieee: 'T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity
learn stimulus intensity statistics,” presented at the NIPS: Neural Information
Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.'
ista: 'Monk T, Savin C, Lücke J. 2016. Neurons equipped with intrinsic plasticity
learn stimulus intensity statistics. NIPS: Neural Information Processing Systems,
Advances in Neural Information Processing Systems, vol. 29, 4285–4293.'
mla: Monk, Travis, et al. Neurons Equipped with Intrinsic Plasticity Learn Stimulus
Intensity Statistics. Vol. 29, Neural Information Processing Systems, 2016,
pp. 4285–93.
short: T. Monk, C. Savin, J. Lücke, in:, Neural Information Processing Systems,
2016, pp. 4285–4293.
conference:
end_date: 2016-12-10
location: Barcelona, Spaine
name: 'NIPS: Neural Information Processing Systems'
start_date: 2016-12-05
date_created: 2018-12-11T11:49:21Z
date_published: 2016-01-01T00:00:00Z
date_updated: 2021-01-12T08:22:08Z
day: '01'
department:
- _id: GaTk
ec_funded: 1
intvolume: ' 29'
language:
- iso: eng
main_file_link:
- url: https://papers.nips.cc/paper/6582-neurons-equipped-with-intrinsic-plasticity-learn-stimulus-intensity-statistics
month: '01'
oa_version: None
page: 4285 - 4293
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication_status: published
publisher: Neural Information Processing Systems
publist_id: '6469'
quality_controlled: '1'
scopus_import: 1
status: public
title: Neurons equipped with intrinsic plasticity learn stimulus intensity statistics
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 29
year: '2016'
...
---
_id: '1270'
abstract:
- lang: eng
text: A crucial step in the early development of multicellular organisms involves
the establishment of spatial patterns of gene expression which later direct proliferating
cells to take on different cell fates. These patterns enable the cells to infer
their global position within a tissue or an organism by reading out local gene
expression levels. The patterning system is thus said to encode positional information,
a concept that was formalized recently in the framework of information theory.
Here we introduce a toy model of patterning in one spatial dimension, which can
be seen as an extension of Wolpert's paradigmatic "French Flag" model,
to patterning by several interacting, spatially coupled genes subject to intrinsic
and extrinsic noise. Our model, a variant of an Ising spin system, allows us to
systematically explore expression patterns that optimally encode positional information.
We find that optimal patterning systems use positional cues, as in the French
Flag model, together with gene-gene interactions to generate combinatorial codes
for position which we call "Counter" patterns. Counter patterns can
also be stabilized against noise and variations in system size or morphogen dosage
by longer-range spatial interactions of the type invoked in the Turing model.
The simple setup proposed here qualitatively captures many of the experimentally
observed properties of biological patterning systems and allows them to be studied
in a single, theoretically consistent framework.
acknowledgement: The authors would like to thank Thomas Sokolowski and Filipe Tostevin
for helpful discussions. PH and UG were funded by the German Excellence Initiative
via the program "Nanosystems Initiative Munich" (https://www.nano-initiative-munich.de)
and the German Research Foundation via the SFB 1032 "Nanoagents for Spatiotemporal
Control of Molecular and Cellular Reactions" (http://www.sfb1032.physik.uni-muenchen.de).
GT was funded by the Austrian Science Fund (FWF P 28844) (http://www.fwf.ac.at).
article_number: e0163628
author:
- first_name: Patrick
full_name: Hillenbrand, Patrick
last_name: Hillenbrand
- first_name: Ulrich
full_name: Gerland, Ulrich
last_name: Gerland
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: 'Hillenbrand P, Gerland U, Tkačik G. Beyond the French flag model: Exploiting
spatial and gene regulatory interactions for positional information. PLoS One.
2016;11(9). doi:10.1371/journal.pone.0163628'
apa: 'Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Beyond the French flag
model: Exploiting spatial and gene regulatory interactions for positional information.
PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628'
chicago: 'Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Beyond the French
Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional
Information.” PLoS One. Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.'
ieee: 'P. Hillenbrand, U. Gerland, and G. Tkačik, “Beyond the French flag model:
Exploiting spatial and gene regulatory interactions for positional information,”
PLoS One, vol. 11, no. 9. Public Library of Science, 2016.'
ista: 'Hillenbrand P, Gerland U, Tkačik G. 2016. Beyond the French flag model: Exploiting
spatial and gene regulatory interactions for positional information. PLoS One.
11(9), e0163628.'
mla: 'Hillenbrand, Patrick, et al. “Beyond the French Flag Model: Exploiting Spatial
and Gene Regulatory Interactions for Positional Information.” PLoS One,
vol. 11, no. 9, e0163628, Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.'
short: P. Hillenbrand, U. Gerland, G. Tkačik, PLoS One 11 (2016).
date_created: 2018-12-11T11:51:03Z
date_published: 2016-09-27T00:00:00Z
date_updated: 2023-02-23T14:11:37Z
day: '27'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0163628
file:
- access_level: open_access
checksum: 3d0d55d373096a033bd9cf79288c8586
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:10:47Z
date_updated: 2020-07-14T12:44:42Z
file_id: '4837'
file_name: IST-2016-696-v1+1_journal.pone.0163628.PDF
file_size: 4950415
relation: main_file
file_date_updated: 2020-07-14T12:44:42Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '6050'
pubrep_id: '696'
quality_controlled: '1'
related_material:
record:
- id: '9869'
relation: research_data
status: public
- id: '9870'
relation: research_data
status: public
- id: '9871'
relation: research_data
status: public
scopus_import: 1
status: public
title: 'Beyond the French flag model: Exploiting spatial and gene regulatory interactions
for positional information'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2016'
...
---
_id: '9870'
abstract:
- lang: eng
text: The effect of noise in the input field on an Ising model is approximated.
Furthermore, methods to compute positional information in an Ising model by transfer
matrices and Monte Carlo sampling are outlined.
article_processing_charge: No
author:
- first_name: Patrick
full_name: Hillenbrand, Patrick
last_name: Hillenbrand
- first_name: Ulrich
full_name: Gerland, Ulrich
last_name: Gerland
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in
an Ising model. 2016. doi:10.1371/journal.pone.0163628.s002
apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional
information in an Ising model. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s002
chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of
Positional Information in an Ising Model.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s002.
ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information
in an Ising model.” Public Library of Science, 2016.
ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information
in an Ising model, Public Library of Science, 10.1371/journal.pone.0163628.s002.
mla: Hillenbrand, Patrick, et al. Computation of Positional Information in an
Ising Model. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s002.
short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016).
date_created: 2021-08-10T09:23:45Z
date_published: 2016-09-27T00:00:00Z
date_updated: 2023-02-21T16:56:40Z
day: '27'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0163628.s002
month: '09'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1270'
relation: used_in_publication
status: public
status: public
title: Computation of positional information in an Ising model
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2016'
...
---
_id: '9869'
abstract:
- lang: eng
text: A lower bound on the error of a positional estimator with limited positional
information is derived.
article_processing_charge: No
author:
- first_name: Patrick
full_name: Hillenbrand, Patrick
last_name: Hillenbrand
- first_name: Ulrich
full_name: Gerland, Ulrich
last_name: Gerland
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Hillenbrand P, Gerland U, Tkačik G. Error bound on an estimator of position.
2016. doi:10.1371/journal.pone.0163628.s001
apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Error bound on an estimator
of position. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s001
chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Error Bound on
an Estimator of Position.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s001.
ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Error bound on an estimator of
position.” Public Library of Science, 2016.
ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Error bound on an estimator of position,
Public Library of Science, 10.1371/journal.pone.0163628.s001.
mla: Hillenbrand, Patrick, et al. Error Bound on an Estimator of Position.
Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s001.
short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016).
date_created: 2021-08-10T08:53:48Z
date_published: 2016-09-27T00:00:00Z
date_updated: 2023-02-21T16:56:40Z
day: '27'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0163628.s001
month: '09'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1270'
relation: used_in_publication
status: public
status: public
title: Error bound on an estimator of position
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2016'
...
---
_id: '9871'
abstract:
- lang: eng
text: The positional information in a discrete morphogen field with Gaussian noise
is computed.
article_processing_charge: No
author:
- first_name: Patrick
full_name: Hillenbrand, Patrick
last_name: Hillenbrand
- first_name: Ulrich
full_name: Gerland, Ulrich
last_name: Gerland
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in
a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003
apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional
information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003
chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of
Positional Information in a Discrete Morphogen Field.” Public Library of Science,
2016. https://doi.org/10.1371/journal.pone.0163628.s003.
ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information
in a discrete morphogen field.” Public Library of Science, 2016.
ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information
in a discrete morphogen field, Public Library of Science, 10.1371/journal.pone.0163628.s003.
mla: Hillenbrand, Patrick, et al. Computation of Positional Information in a
Discrete Morphogen Field. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s003.
short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016).
date_created: 2021-08-10T09:27:35Z
date_updated: 2023-02-21T16:56:40Z
day: '27'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0163628.s003
month: '09'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1270'
relation: used_in_publication
status: public
status: public
title: Computation of positional information in a discrete morphogen field
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2016'
...
---
_id: '1128'
abstract:
- lang: eng
text: "The process of gene expression is central to the modern understanding of
how cellular systems\r\nfunction. In this process, a special kind of regulatory
proteins, called transcription factors,\r\nare important to determine how much
protein is produced from a given gene. As biological\r\ninformation is transmitted
from transcription factor concentration to mRNA levels to amounts of\r\nprotein,
various sources of noise arise and pose limits to the fidelity of intracellular
signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene
expression: (i) the mathematical\r\ndescription of complex promoters responsible
for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information
processing the cell faces due to the interference from multiple\r\nfluctuating
signals, (iii) how the presence of gene expression noise influences the evolution\r\nof
regulatory sequences, (iv) and tools for the experimental study of origins and
consequences\r\nof cell-cell heterogeneity, including an application to bacterial
stress response systems."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
citation:
ama: Rieckh G. Studying the complexities of transcriptional regulation. 2016.
apa: Rieckh, G. (2016). Studying the complexities of transcriptional regulation.
Institute of Science and Technology Austria.
chicago: Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.”
Institute of Science and Technology Austria, 2016.
ieee: G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute
of Science and Technology Austria, 2016.
ista: Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute
of Science and Technology Austria.
mla: Rieckh, Georg. Studying the Complexities of Transcriptional Regulation.
Institute of Science and Technology Austria, 2016.
short: G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute
of Science and Technology Austria, 2016.
date_created: 2018-12-11T11:50:18Z
date_published: 2016-08-01T00:00:00Z
date_updated: 2023-09-07T11:44:34Z
day: '01'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GaTk
file:
- access_level: closed
checksum: ec453918c3bf8e6f460fd1156ef7b493
content_type: application/pdf
creator: dernst
date_created: 2019-08-13T11:46:25Z
date_updated: 2019-08-13T11:46:25Z
file_id: '6815'
file_name: Thesis_Georg_Rieckh_w_signature_page.pdf
file_size: 2614660
relation: main_file
- access_level: open_access
checksum: 51ae398166370d18fd22478b6365c4da
content_type: application/pdf
creator: dernst
date_created: 2020-09-21T11:30:40Z
date_updated: 2020-09-21T11:30:40Z
file_id: '8542'
file_name: Thesis_Georg_Rieckh.pdf
file_size: 6096178
relation: main_file
success: 1
file_date_updated: 2020-09-21T11:30:40Z
has_accepted_license: '1'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: '114'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
publist_id: '6232'
status: public
supervisor:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
title: Studying the complexities of transcriptional regulation
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2016'
...
---
_id: '1358'
abstract:
- lang: eng
text: 'Gene regulation relies on the specificity of transcription factor (TF)–DNA
interactions. Limited specificity may lead to crosstalk: a regulatory state in
which a gene is either incorrectly activated due to noncognate TF–DNA interactions
or remains erroneously inactive. As each TF can have numerous interactions with
noncognate cis-regulatory elements, crosstalk is inherently a global problem,
yet has previously not been studied as such. We construct a theoretical framework
to analyse the effects of global crosstalk on gene regulation. We find that crosstalk
presents a significant challenge for organisms with low-specificity TFs, such
as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting
at equilibrium, including variants of cooperativity and combinatorial regulation.
Our results suggest that crosstalk imposes a previously unexplored global constraint
on the functioning and evolution of regulatory networks, which is qualitatively
distinct from the known constraints that act at the level of individual gene regulatory
elements.'
article_number: '12307'
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to
gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307
apa: Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016).
Intrinsic limits to gene regulation by global crosstalk. Nature Communications.
Nature Publishing Group. https://doi.org/10.1038/ncomms12307
chicago: Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and
Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature
Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307.
ieee: T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic
limits to gene regulation by global crosstalk,” Nature Communications,
vol. 7. Nature Publishing Group, 2016.
ista: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits
to gene regulation by global crosstalk. Nature Communications. 7, 12307.
mla: Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.”
Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307.
short: T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications
7 (2016).
date_created: 2018-12-11T11:51:34Z
date_published: 2016-08-04T00:00:00Z
date_updated: 2023-09-07T12:53:49Z
day: '04'
ddc:
- '576'
department:
- _id: GaTk
- _id: NiBa
- _id: CaGu
doi: 10.1038/ncomms12307
ec_funded: 1
file:
- access_level: open_access
checksum: fe3f3a1526d180b29fe691ab11435b78
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:01Z
date_updated: 2020-07-14T12:44:46Z
file_id: '4919'
file_name: IST-2016-627-v1+1_ncomms12307.pdf
file_size: 861805
relation: main_file
- access_level: open_access
checksum: 164864a1a675f3ad80e9917c27aba07f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:02Z
date_updated: 2020-07-14T12:44:46Z
file_id: '4920'
file_name: IST-2016-627-v1+2_ncomms12307-s1.pdf
file_size: 1084703
relation: main_file
file_date_updated: 2020-07-14T12:44:46Z
has_accepted_license: '1'
intvolume: ' 7'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_status: published
publisher: Nature Publishing Group
publist_id: '5887'
pubrep_id: '627'
quality_controlled: '1'
related_material:
record:
- id: '6071'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Intrinsic limits to gene regulation by global crosstalk
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2016'
...
---
_id: '10794'
abstract:
- lang: eng
text: Mathematical models are of fundamental importance in the understanding of
complex population dynamics. For instance, they can be used to predict the population
evolution starting from different initial conditions or to test how a system responds
to external perturbations. For this analysis to be meaningful in real applications,
however, it is of paramount importance to choose an appropriate model structure
and to infer the model parameters from measured data. While many parameter inference
methods are available for models based on deterministic ordinary differential
equations, the same does not hold for more detailed individual-based models. Here
we consider, in particular, stochastic models in which the time evolution of the
species abundances is described by a continuous-time Markov chain. These models
are governed by a master equation that is typically difficult to solve. Consequently,
traditional inference methods that rely on iterative evaluation of parameter likelihoods
are computationally intractable. The aim of this paper is to present recent advances
in parameter inference for continuous-time Markov chain models, based on a moment
closure approximation of the parameter likelihood, and to investigate how these
results can help in understanding, and ultimately controlling, complex systems
in ecology. Specifically, we illustrate through an agricultural pest case study
how parameters of a stochastic individual-based model can be identified from measured
data and how the resulting model can be used to solve an optimal control problem
in a stochastic setting. In particular, we show how the matter of determining
the optimal combination of two different pest control methods can be formulated
as a chance constrained optimization problem where the control action is modeled
as a state reset, leading to a hybrid system formulation.
acknowledgement: "The authors would like to acknowledge contributions from Baptiste
Mottet who performed preliminary analysis regarding parameter inference for the
considered case study in a student project (Mottet, 2014/2015).\r\nThe research
leading to these results has received funding from the People Programme (Marie Curie
Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under
REA grant agreement No. [291734] and from SystemsX under the project SignalX."
article_number: '42'
article_processing_charge: No
article_type: original
author:
- first_name: Francesca
full_name: Parise, Francesca
last_name: Parise
- first_name: John
full_name: Lygeros, John
last_name: Lygeros
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
citation:
ama: 'Parise F, Lygeros J, Ruess J. Bayesian inference for stochastic individual-based
models of ecological systems: a pest control simulation study. Frontiers in
Environmental Science. 2015;3. doi:10.3389/fenvs.2015.00042'
apa: 'Parise, F., Lygeros, J., & Ruess, J. (2015). Bayesian inference for stochastic
individual-based models of ecological systems: a pest control simulation study.
Frontiers in Environmental Science. Frontiers. https://doi.org/10.3389/fenvs.2015.00042'
chicago: 'Parise, Francesca, John Lygeros, and Jakob Ruess. “Bayesian Inference
for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation
Study.” Frontiers in Environmental Science. Frontiers, 2015. https://doi.org/10.3389/fenvs.2015.00042.'
ieee: 'F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based
models of ecological systems: a pest control simulation study,” Frontiers in
Environmental Science, vol. 3. Frontiers, 2015.'
ista: 'Parise F, Lygeros J, Ruess J. 2015. Bayesian inference for stochastic individual-based
models of ecological systems: a pest control simulation study. Frontiers in Environmental
Science. 3, 42.'
mla: 'Parise, Francesca, et al. “Bayesian Inference for Stochastic Individual-Based
Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in
Environmental Science, vol. 3, 42, Frontiers, 2015, doi:10.3389/fenvs.2015.00042.'
short: F. Parise, J. Lygeros, J. Ruess, Frontiers in Environmental Science 3 (2015).
date_created: 2022-02-25T11:42:25Z
date_published: 2015-06-10T00:00:00Z
date_updated: 2022-02-25T11:59:23Z
day: '10'
ddc:
- '000'
- '570'
department:
- _id: ToHe
- _id: GaTk
doi: 10.3389/fenvs.2015.00042
ec_funded: 1
file:
- access_level: open_access
checksum: 26c222487564e1be02a11d688d6f769d
content_type: application/pdf
creator: dernst
date_created: 2022-02-25T11:55:26Z
date_updated: 2022-02-25T11:55:26Z
file_id: '10795'
file_name: 2015_FrontiersEnvironmScience_Parise.pdf
file_size: 1371201
relation: main_file
success: 1
file_date_updated: 2022-02-25T11:55:26Z
has_accepted_license: '1'
intvolume: ' 3'
keyword:
- General Environmental Science
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Frontiers in Environmental Science
publication_identifier:
issn:
- 2296-665X
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Bayesian inference for stochastic individual-based models of ecological systems:
a pest control simulation study'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2015'
...
---
_id: '1539'
abstract:
- lang: eng
text: 'Many stochastic models of biochemical reaction networks contain some chemical
species for which the number of molecules that are present in the system can only
be finite (for instance due to conservation laws), but also other species that
can be present in arbitrarily large amounts. The prime example of such networks
are models of gene expression, which typically contain a small and finite number
of possible states for the promoter but an infinite number of possible states
for the amount of mRNA and protein. One of the main approaches to analyze such
models is through the use of equations for the time evolution of moments of the
chemical species. Recently, a new approach based on conditional moments of the
species with infinite state space given all the different possible states of the
finite species has been proposed. It was argued that this approach allows one
to capture more details about the full underlying probability distribution with
a smaller number of equations. Here, I show that the result that less moments
provide more information can only stem from an unnecessarily complicated description
of the system in the classical formulation. The foundation of this argument will
be the derivation of moment equations that describe the complete probability distribution
over the finite state space but only low-order moments over the infinite state
space. I will show that the number of equations that is needed is always less
than what was previously claimed and always less than the number of conditional
moment equations up to the same order. To support these arguments, a symbolic
algorithm is provided that can be used to derive minimal systems of unconditional
moment equations for models with partially finite state space. '
article_number: '244103'
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
citation:
ama: Ruess J. Minimal moment equations for stochastic models of biochemical reaction
networks with partially finite state space. Journal of Chemical Physics.
2015;143(24). doi:10.1063/1.4937937
apa: Ruess, J. (2015). Minimal moment equations for stochastic models of biochemical
reaction networks with partially finite state space. Journal of Chemical Physics.
American Institute of Physics. https://doi.org/10.1063/1.4937937
chicago: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical
Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics.
American Institute of Physics, 2015. https://doi.org/10.1063/1.4937937.
ieee: J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction
networks with partially finite state space,” Journal of Chemical Physics,
vol. 143, no. 24. American Institute of Physics, 2015.
ista: Ruess J. 2015. Minimal moment equations for stochastic models of biochemical
reaction networks with partially finite state space. Journal of Chemical Physics.
143(24), 244103.
mla: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical
Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics,
vol. 143, no. 24, 244103, American Institute of Physics, 2015, doi:10.1063/1.4937937.
short: J. Ruess, Journal of Chemical Physics 143 (2015).
date_created: 2018-12-11T11:52:36Z
date_published: 2015-12-22T00:00:00Z
date_updated: 2021-01-12T06:51:28Z
day: '22'
ddc:
- '000'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1063/1.4937937
ec_funded: 1
file:
- access_level: open_access
checksum: 838657118ae286463a2b7737319f35ce
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:07:43Z
date_updated: 2020-07-14T12:45:01Z
file_id: '4641'
file_name: IST-2016-593-v1+1_Minimal_moment_equations.pdf
file_size: 605355
relation: main_file
file_date_updated: 2020-07-14T12:45:01Z
has_accepted_license: '1'
intvolume: ' 143'
issue: '24'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25EE3708-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '267989'
name: Quantitative Reactive Modeling
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Journal of Chemical Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '5632'
pubrep_id: '593'
quality_controlled: '1'
scopus_import: 1
status: public
title: Minimal moment equations for stochastic models of biochemical reaction networks
with partially finite state space
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 143
year: '2015'
...
---
_id: '1538'
abstract:
- lang: eng
text: Systems biology rests on the idea that biological complexity can be better
unraveled through the interplay of modeling and experimentation. However, the
success of this approach depends critically on the informativeness of the chosen
experiments, which is usually unknown a priori. Here, we propose a systematic
scheme based on iterations of optimal experiment design, flow cytometry experiments,
and Bayesian parameter inference to guide the discovery process in the case of
stochastic biochemical reaction networks. To illustrate the benefit of our methodology,
we apply it to the characterization of an engineered light-inducible gene expression
circuit in yeast and compare the performance of the resulting model with models
identified from nonoptimal experiments. In particular, we compare the parameter
posterior distributions and the precision to which the outcome of future experiments
can be predicted. Moreover, we illustrate how the identified stochastic model
can be used to determine light induction patterns that make either the average
amount of protein or the variability in a population of cells follow a desired
profile. Our results show that optimal experiment design allows one to derive
models that are accurate enough to precisely predict and regulate the protein
expression in heterogeneous cell populations over extended periods of time.
acknowledgement: 'J.R., F.P., and J.L. acknowledge support from the European Commission
under the Network of Excellence HYCON2 (highly-complex and networked control systems)
and SystemsX.ch under the SignalX Project. J.R. acknowledges support from the People
Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme
FP7/2007-2013 under REA (Research Executive Agency) Grant 291734. M.K. acknowledges
support from Human Frontier Science Program Grant RP0061/2011 (www.hfsp.org). '
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Francesca
full_name: Parise, Francesca
last_name: Parise
- first_name: Andreas
full_name: Milias Argeitis, Andreas
last_name: Milias Argeitis
- first_name: Mustafa
full_name: Khammash, Mustafa
last_name: Khammash
- first_name: John
full_name: Lygeros, John
last_name: Lygeros
citation:
ama: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment
design guides the characterization of a light-inducible gene expression circuit.
PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112
apa: Ruess, J., Parise, F., Milias Argeitis, A., Khammash, M., & Lygeros, J.
(2015). Iterative experiment design guides the characterization of a light-inducible
gene expression circuit. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1423947112
chicago: Ruess, Jakob, Francesca Parise, Andreas Milias Argeitis, Mustafa Khammash,
and John Lygeros. “Iterative Experiment Design Guides the Characterization of
a Light-Inducible Gene Expression Circuit.” PNAS. National Academy of Sciences,
2015. https://doi.org/10.1073/pnas.1423947112.
ieee: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative
experiment design guides the characterization of a light-inducible gene expression
circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153,
2015.
ista: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative
experiment design guides the characterization of a light-inducible gene expression
circuit. PNAS. 112(26), 8148–8153.
mla: Ruess, Jakob, et al. “Iterative Experiment Design Guides the Characterization
of a Light-Inducible Gene Expression Circuit.” PNAS, vol. 112, no. 26,
National Academy of Sciences, 2015, pp. 8148–53, doi:10.1073/pnas.1423947112.
short: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112
(2015) 8148–8153.
date_created: 2018-12-11T11:52:36Z
date_published: 2015-06-30T00:00:00Z
date_updated: 2021-01-12T06:51:27Z
day: '30'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1073/pnas.1423947112
ec_funded: 1
external_id:
pmid:
- '26085136'
intvolume: ' 112'
issue: '26'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491780/
month: '06'
oa: 1
oa_version: Submitted Version
page: 8148 - 8153
pmid: 1
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '5633'
quality_controlled: '1'
scopus_import: 1
status: public
title: Iterative experiment design guides the characterization of a light-inducible
gene expression circuit
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 112
year: '2015'
...
---
_id: '1564'
article_number: '145'
author:
- first_name: Matthieu
full_name: Gilson, Matthieu
last_name: Gilson
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Friedemann
full_name: Zenke, Friedemann
last_name: Zenke
citation:
ama: 'Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the
interaction of different forms of plasticity. Frontiers in Computational Neuroscience.
2015;9(11). doi:10.3389/fncom.2015.00145'
apa: 'Gilson, M., Savin, C., & Zenke, F. (2015). Editorial: Emergent neural
computation from the interaction of different forms of plasticity. Frontiers
in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2015.00145'
chicago: 'Gilson, Matthieu, Cristina Savin, and Friedemann Zenke. “Editorial: Emergent
Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers
in Computational Neuroscience. Frontiers Research Foundation, 2015. https://doi.org/10.3389/fncom.2015.00145.'
ieee: 'M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation
from the interaction of different forms of plasticity,” Frontiers in Computational
Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.'
ista: 'Gilson M, Savin C, Zenke F. 2015. Editorial: Emergent neural computation
from the interaction of different forms of plasticity. Frontiers in Computational
Neuroscience. 9(11), 145.'
mla: 'Gilson, Matthieu, et al. “Editorial: Emergent Neural Computation from the
Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience,
vol. 9, no. 11, 145, Frontiers Research Foundation, 2015, doi:10.3389/fncom.2015.00145.'
short: M. Gilson, C. Savin, F. Zenke, Frontiers in Computational Neuroscience 9
(2015).
date_created: 2018-12-11T11:52:45Z
date_published: 2015-11-30T00:00:00Z
date_updated: 2021-01-12T06:51:37Z
day: '30'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.3389/fncom.2015.00145
ec_funded: 1
file:
- access_level: open_access
checksum: cea73b6d3ef1579f32da10b82f4de4fd
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:09Z
date_updated: 2020-07-14T12:45:02Z
file_id: '4927'
file_name: IST-2016-479-v1+1_fncom-09-00145.pdf
file_size: 187038
relation: main_file
file_date_updated: 2020-07-14T12:45:02Z
has_accepted_license: '1'
intvolume: ' 9'
issue: '11'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Frontiers in Computational Neuroscience
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '5607'
pubrep_id: '479'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Editorial: Emergent neural computation from the interaction of different forms
of plasticity'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2015'
...
---
_id: '1570'
abstract:
- lang: eng
text: Grounding autonomous behavior in the nervous system is a fundamental challenge
for neuroscience. In particular, self-organized behavioral development provides
more questions than answers. Are there special functional units for curiosity,
motivation, and creativity? This paper argues that these features can be grounded
in synaptic plasticity itself, without requiring any higher-level constructs.
We propose differential extrinsic plasticity (DEP) as a new synaptic rule for
self-learning systems and apply it to a number of complex robotic systems as a
test case. Without specifying any purpose or goal, seemingly purposeful and adaptive
rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence.
These surprising results require no systemspecific modifications of the DEP rule.
They rather arise from the underlying mechanism of spontaneous symmetry breaking,which
is due to the tight brain body environment coupling. The new synaptic rule is
biologically plausible and would be an interesting target for neurobiological
investigation. We also argue that this neuronal mechanism may have been a catalyst
in natural evolution.
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: Der R, Martius GS. Novel plasticity rule can explain the development of sensorimotor
intelligence. PNAS. 2015;112(45):E6224-E6232. doi:10.1073/pnas.1508400112
apa: Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the
development of sensorimotor intelligence. PNAS. National Academy of Sciences.
https://doi.org/10.1073/pnas.1508400112
chicago: Der, Ralf, and Georg S Martius. “Novel Plasticity Rule Can Explain the
Development of Sensorimotor Intelligence.” PNAS. National Academy of Sciences,
2015. https://doi.org/10.1073/pnas.1508400112.
ieee: R. Der and G. S. Martius, “Novel plasticity rule can explain the development
of sensorimotor intelligence,” PNAS, vol. 112, no. 45. National Academy
of Sciences, pp. E6224–E6232, 2015.
ista: Der R, Martius GS. 2015. Novel plasticity rule can explain the development
of sensorimotor intelligence. PNAS. 112(45), E6224–E6232.
mla: Der, Ralf, and Georg S. Martius. “Novel Plasticity Rule Can Explain the Development
of Sensorimotor Intelligence.” PNAS, vol. 112, no. 45, National Academy
of Sciences, 2015, pp. E6224–32, doi:10.1073/pnas.1508400112.
short: R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232.
date_created: 2018-12-11T11:52:47Z
date_published: 2015-11-10T00:00:00Z
date_updated: 2021-01-12T06:51:40Z
day: '10'
department:
- _id: ChLa
- _id: GaTk
doi: 10.1073/pnas.1508400112
ec_funded: 1
external_id:
pmid:
- '26504200'
intvolume: ' 112'
issue: '45'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653169/
month: '11'
oa: 1
oa_version: Submitted Version
page: E6224 - E6232
pmid: 1
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '5601'
quality_controlled: '1'
scopus_import: 1
status: public
title: Novel plasticity rule can explain the development of sensorimotor intelligence
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 112
year: '2015'
...
---
_id: '1658'
abstract:
- lang: eng
text: Continuous-time Markov chain (CTMC) models have become a central tool for
understanding the dynamics of complex reaction networks and the importance of
stochasticity in the underlying biochemical processes. When such models are employed
to answer questions in applications, in order to ensure that the model provides
a sufficiently accurate representation of the real system, it is of vital importance
that the model parameters are inferred from real measured data. This, however,
is often a formidable task and all of the existing methods fail in one case or
the other, usually because the underlying CTMC model is high-dimensional and computationally
difficult to analyze. The parameter inference methods that tend to scale best
in the dimension of the CTMC are based on so-called moment closure approximations.
However, there exists a large number of different moment closure approximations
and it is typically hard to say a priori which of the approximations is the most
suitable for the inference procedure. Here, we propose a moment-based parameter
inference method that automatically chooses the most appropriate moment closure
method. Accordingly, contrary to existing methods, the user is not required to
be experienced in moment closure techniques. In addition to that, our method adaptively
changes the approximation during the parameter inference to ensure that always
the best approximation is used, even in cases where different approximations are
best in different regions of the parameter space.
alternative_title:
- LNCS
author:
- first_name: Sergiy
full_name: Bogomolov, Sergiy
id: 369D9A44-F248-11E8-B48F-1D18A9856A87
last_name: Bogomolov
orcid: 0000-0002-0686-0365
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000−0002−2985−7724
- first_name: Andreas
full_name: Podelski, Andreas
last_name: Podelski
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Christian
full_name: Schilling, Christian
last_name: Schilling
citation:
ama: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. Adaptive moment
closure for parameter inference of biochemical reaction networks. 2015;9308:77-89.
doi:10.1007/978-3-319-23401-4_8
apa: 'Bogomolov, S., Henzinger, T. A., Podelski, A., Ruess, J., & Schilling,
C. (2015). Adaptive moment closure for parameter inference of biochemical reaction
networks. Presented at the CMSB: Computational Methods in Systems Biology, Nantes,
France: Springer. https://doi.org/10.1007/978-3-319-23401-4_8'
chicago: Bogomolov, Sergiy, Thomas A Henzinger, Andreas Podelski, Jakob Ruess, and
Christian Schilling. “Adaptive Moment Closure for Parameter Inference of Biochemical
Reaction Networks.” Lecture Notes in Computer Science. Springer, 2015. https://doi.org/10.1007/978-3-319-23401-4_8.
ieee: S. Bogomolov, T. A. Henzinger, A. Podelski, J. Ruess, and C. Schilling, “Adaptive
moment closure for parameter inference of biochemical reaction networks,” vol.
9308. Springer, pp. 77–89, 2015.
ista: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. 2015. Adaptive
moment closure for parameter inference of biochemical reaction networks. 9308,
77–89.
mla: Bogomolov, Sergiy, et al. Adaptive Moment Closure for Parameter Inference
of Biochemical Reaction Networks. Vol. 9308, Springer, 2015, pp. 77–89, doi:10.1007/978-3-319-23401-4_8.
short: S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, C. Schilling, 9308 (2015)
77–89.
conference:
end_date: 2015-09-18
location: Nantes, France
name: 'CMSB: Computational Methods in Systems Biology'
start_date: 2015-09-16
date_created: 2018-12-11T11:53:18Z
date_published: 2015-09-01T00:00:00Z
date_updated: 2023-02-21T16:17:24Z
day: '01'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1007/978-3-319-23401-4_8
ec_funded: 1
intvolume: ' 9308'
language:
- iso: eng
month: '09'
oa_version: None
page: 77 - 89
project:
- _id: 25EE3708-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '267989'
name: Quantitative Reactive Modeling
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication_status: published
publisher: Springer
publist_id: '5492'
quality_controlled: '1'
related_material:
record:
- id: '1148'
relation: later_version
status: public
scopus_import: 1
series_title: Lecture Notes in Computer Science
status: public
title: Adaptive moment closure for parameter inference of biochemical reaction networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9308
year: '2015'
...
---
_id: '1697'
abstract:
- lang: eng
text: Motion tracking is a challenge the visual system has to solve by reading out
the retinal population. It is still unclear how the information from different
neurons can be combined together to estimate the position of an object. Here we
recorded a large population of ganglion cells in a dense patch of salamander and
guinea pig retinas while displaying a bar moving diffusively. We show that the
bar’s position can be reconstructed from retinal activity with a precision in
the hyperacuity regime using a linear decoder acting on 100+ cells. We then took
advantage of this unprecedented precision to explore the spatial structure of
the retina’s population code. The classical view would have suggested that the
firing rates of the cells form a moving hill of activity tracking the bar’s position.
Instead, we found that most ganglion cells in the salamander fired sparsely and
idiosyncratically, so that their neural image did not track the bar. Furthermore,
ganglion cell activity spanned an area much larger than predicted by their receptive
fields, with cells coding for motion far in their surround. As a result, population
redundancy was high, and we could find multiple, disjoint subsets of neurons that
encoded the trajectory with high precision. This organization allows for diverse
collections of ganglion cells to represent high-accuracy motion information in
a form easily read out by downstream neural circuits.
acknowledgement: 'This work was supported by grants EY 014196 and EY 017934 to MJB,
ANR OPTIMA, the French State program Investissements d’Avenir managed by the Agence
Nationale de la Recherche [LIFESENSES: ANR-10-LABX-65], and by a EC grant from the
Human Brain Project (CLAP) to OM, the Austrian Research Foundation FWF P25651 to
VBS and GT. VBS is partially supported by contracts MEC, Spain (Grant No. AYA2010-
22111-C03-02, Grant No. AYA2013-48623-C2-2 and FEDER Funds).'
article_number: e1004304
author:
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Kristina
full_name: Simmons, Kristina
last_name: Simmons
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
citation:
ama: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. High accuracy
decoding of dynamical motion from a large retinal population. PLoS Computational
Biology. 2015;11(7). doi:10.1371/journal.pcbi.1004304
apa: Marre, O., Botella Soler, V., Simmons, K., Mora, T., Tkačik, G., & Berry,
M. (2015). High accuracy decoding of dynamical motion from a large retinal population.
PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004304
chicago: Marre, Olivier, Vicente Botella Soler, Kristina Simmons, Thierry Mora,
Gašper Tkačik, and Michael Berry. “High Accuracy Decoding of Dynamical Motion
from a Large Retinal Population.” PLoS Computational Biology. Public Library
of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004304.
ieee: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, and M. Berry,
“High accuracy decoding of dynamical motion from a large retinal population,”
PLoS Computational Biology, vol. 11, no. 7. Public Library of Science,
2015.
ista: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. 2015. High
accuracy decoding of dynamical motion from a large retinal population. PLoS Computational
Biology. 11(7), e1004304.
mla: Marre, Olivier, et al. “High Accuracy Decoding of Dynamical Motion from a Large
Retinal Population.” PLoS Computational Biology, vol. 11, no. 7, e1004304,
Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004304.
short: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, M. Berry, PLoS
Computational Biology 11 (2015).
date_created: 2018-12-11T11:53:31Z
date_published: 2015-07-01T00:00:00Z
date_updated: 2021-01-12T06:52:35Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1004304
file:
- access_level: open_access
checksum: 472b979f3f1cffb37b3e503f085115ca
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:25Z
date_updated: 2020-07-14T12:45:12Z
file_id: '5212'
file_name: IST-2016-455-v1+1_journal.pcbi.1004304.pdf
file_size: 4673930
relation: main_file
file_date_updated: 2020-07-14T12:45:12Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '5447'
pubrep_id: '455'
quality_controlled: '1'
scopus_import: 1
status: public
title: High accuracy decoding of dynamical motion from a large retinal population
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2015'
...
---
_id: '1701'
abstract:
- lang: eng
text: 'The activity of a neural network is defined by patterns of spiking and silence
from the individual neurons. Because spikes are (relatively) sparse, patterns
of activity with increasing numbers of spikes are less probable, but, with more
spikes, the number of possible patterns increases. This tradeoff between probability
and numerosity is mathematically equivalent to the relationship between entropy
and energy in statistical physics. We construct this relationship for populations
of up to N = 160 neurons in a small patch of the vertebrate retina, using a combination
of direct and model-based analyses of experiments on the response of this network
to naturalistic movies. We see signs of a thermodynamic limit, where the entropy
per neuron approaches a smooth function of the energy per neuron as N increases.
The form of this function corresponds to the distribution of activity being poised
near an unusual kind of critical point. We suggest further tests of criticality,
and give a brief discussion of its functional significance. '
acknowledgement: "Research was supported in part by National Science Foundation Grants
PHY-1305525, PHY-1451171, and CCF-0939370, by National Institutes of Health Grant
R01 EY14196, and by Austrian Science Foundation Grant FWF P25651. Additional support
was provided by the\r\nFannie and John Hertz Foundation, by the Swartz Foundation,
by the W. M. Keck Foundation, and by the Simons Foundation."
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Dario
full_name: Amodei, Dario
last_name: Amodei
- first_name: Stephanie
full_name: Palmer, Stephanie
last_name: Palmer
- first_name: Michael
full_name: Berry Ii, Michael
last_name: Berry Ii
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Tkačik G, Mora T, Marre O, et al. Thermodynamics and signatures of criticality
in a network of neurons. PNAS. 2015;112(37):11508-11513. doi:10.1073/pnas.1514188112
apa: Tkačik, G., Mora, T., Marre, O., Amodei, D., Palmer, S., Berry Ii, M., &
Bialek, W. (2015). Thermodynamics and signatures of criticality in a network of
neurons. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1514188112
chicago: Tkačik, Gašper, Thierry Mora, Olivier Marre, Dario Amodei, Stephanie Palmer,
Michael Berry Ii, and William Bialek. “Thermodynamics and Signatures of Criticality
in a Network of Neurons.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1514188112.
ieee: G. Tkačik et al., “Thermodynamics and signatures of criticality in
a network of neurons,” PNAS, vol. 112, no. 37. National Academy of Sciences,
pp. 11508–11513, 2015.
ista: Tkačik G, Mora T, Marre O, Amodei D, Palmer S, Berry Ii M, Bialek W. 2015.
Thermodynamics and signatures of criticality in a network of neurons. PNAS. 112(37),
11508–11513.
mla: Tkačik, Gašper, et al. “Thermodynamics and Signatures of Criticality in a Network
of Neurons.” PNAS, vol. 112, no. 37, National Academy of Sciences, 2015,
pp. 11508–13, doi:10.1073/pnas.1514188112.
short: G. Tkačik, T. Mora, O. Marre, D. Amodei, S. Palmer, M. Berry Ii, W. Bialek,
PNAS 112 (2015) 11508–11513.
date_created: 2018-12-11T11:53:33Z
date_published: 2015-09-15T00:00:00Z
date_updated: 2021-01-12T06:52:37Z
day: '15'
department:
- _id: GaTk
doi: 10.1073/pnas.1514188112
external_id:
pmid:
- '26330611'
intvolume: ' 112'
issue: '37'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577210/
month: '09'
oa: 1
oa_version: Submitted Version
page: 11508 - 11513
pmid: 1
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '5440'
quality_controlled: '1'
scopus_import: 1
status: public
title: Thermodynamics and signatures of criticality in a network of neurons
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 112
year: '2015'
...
---
_id: '1861'
abstract:
- lang: eng
text: Continuous-time Markov chains are commonly used in practice for modeling biochemical
reaction networks in which the inherent randomness of themolecular interactions
cannot be ignored. This has motivated recent research effort into methods for
parameter inference and experiment design for such models. The major difficulty
is that such methods usually require one to iteratively solve the chemical master
equation that governs the time evolution of the probability distribution of the
system. This, however, is rarely possible, and even approximation techniques remain
limited to relatively small and simple systems. An alternative explored in this
article is to base methods on only some low-order moments of the entire probability
distribution. We summarize the theory behind such moment-based methods for parameter
inference and experiment design and provide new case studies where we investigate
their performance.
acknowledgement: "HYCON2; EC; European Commission\r\n"
article_number: '8'
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: John
full_name: Lygeros, John
last_name: Lygeros
citation:
ama: Ruess J, Lygeros J. Moment-based methods for parameter inference and experiment
design for stochastic biochemical reaction networks. ACM Transactions on Modeling
and Computer Simulation. 2015;25(2). doi:10.1145/2688906
apa: Ruess, J., & Lygeros, J. (2015). Moment-based methods for parameter inference
and experiment design for stochastic biochemical reaction networks. ACM Transactions
on Modeling and Computer Simulation. ACM. https://doi.org/10.1145/2688906
chicago: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference
and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions
on Modeling and Computer Simulation. ACM, 2015. https://doi.org/10.1145/2688906.
ieee: J. Ruess and J. Lygeros, “Moment-based methods for parameter inference and
experiment design for stochastic biochemical reaction networks,” ACM Transactions
on Modeling and Computer Simulation, vol. 25, no. 2. ACM, 2015.
ista: Ruess J, Lygeros J. 2015. Moment-based methods for parameter inference and
experiment design for stochastic biochemical reaction networks. ACM Transactions
on Modeling and Computer Simulation. 25(2), 8.
mla: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference
and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions
on Modeling and Computer Simulation, vol. 25, no. 2, 8, ACM, 2015, doi:10.1145/2688906.
short: J. Ruess, J. Lygeros, ACM Transactions on Modeling and Computer Simulation
25 (2015).
date_created: 2018-12-11T11:54:25Z
date_published: 2015-02-01T00:00:00Z
date_updated: 2021-01-12T06:53:41Z
day: '01'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1145/2688906
intvolume: ' 25'
issue: '2'
language:
- iso: eng
month: '02'
oa_version: None
publication: ACM Transactions on Modeling and Computer Simulation
publication_status: published
publisher: ACM
publist_id: '5238'
quality_controlled: '1'
scopus_import: 1
status: public
title: Moment-based methods for parameter inference and experiment design for stochastic
biochemical reaction networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 25
year: '2015'
...
---
_id: '1885'
abstract:
- lang: eng
text: 'The concept of positional information is central to our understanding of
how cells determine their location in a multicellular structure and thereby their
developmental fates. Nevertheless, positional information has neither been defined
mathematically nor quantified in a principled way. Here we provide an information-theoretic
definition in the context of developmental gene expression patterns and examine
the features of expression patterns that affect positional information quantitatively.
We connect positional information with the concept of positional error and develop
tools to directly measure information and error from experimental data. We illustrate
our framework for the case of gap gene expression patterns in the early Drosophila
embryo and show how information that is distributed among only four genes is sufficient
to determine developmental fates with nearly single-cell resolution. Our approach
can be generalized to a variety of different model systems; procedures and examples
are discussed in detail. '
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Julien
full_name: Dubuis, Julien
last_name: Dubuis
- first_name: Mariela
full_name: Petkova, Mariela
last_name: Petkova
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
citation:
ama: 'Tkačik G, Dubuis J, Petkova M, Gregor T. Positional information, positional
error, and readout precision in morphogenesis: A mathematical framework. Genetics.
2015;199(1):39-59. doi:10.1534/genetics.114.171850'
apa: 'Tkačik, G., Dubuis, J., Petkova, M., & Gregor, T. (2015). Positional information,
positional error, and readout precision in morphogenesis: A mathematical framework.
Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.114.171850'
chicago: 'Tkačik, Gašper, Julien Dubuis, Mariela Petkova, and Thomas Gregor. “Positional
Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical
Framework.” Genetics. Genetics Society of America, 2015. https://doi.org/10.1534/genetics.114.171850.'
ieee: 'G. Tkačik, J. Dubuis, M. Petkova, and T. Gregor, “Positional information,
positional error, and readout precision in morphogenesis: A mathematical framework,”
Genetics, vol. 199, no. 1. Genetics Society of America, pp. 39–59, 2015.'
ista: 'Tkačik G, Dubuis J, Petkova M, Gregor T. 2015. Positional information, positional
error, and readout precision in morphogenesis: A mathematical framework. Genetics.
199(1), 39–59.'
mla: 'Tkačik, Gašper, et al. “Positional Information, Positional Error, and Readout
Precision in Morphogenesis: A Mathematical Framework.” Genetics, vol. 199,
no. 1, Genetics Society of America, 2015, pp. 39–59, doi:10.1534/genetics.114.171850.'
short: G. Tkačik, J. Dubuis, M. Petkova, T. Gregor, Genetics 199 (2015) 39–59.
date_created: 2018-12-11T11:54:32Z
date_published: 2015-01-01T00:00:00Z
date_updated: 2021-01-12T06:53:50Z
day: '01'
department:
- _id: GaTk
doi: 10.1534/genetics.114.171850
intvolume: ' 199'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1404.5599
month: '01'
oa: 1
oa_version: Preprint
page: 39 - 59
publication: Genetics
publication_status: published
publisher: Genetics Society of America
publist_id: '5210'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Positional information, positional error, and readout precision in morphogenesis:
A mathematical framework'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 199
year: '2015'
...
---
_id: '1940'
abstract:
- lang: eng
text: We typically think of cells as responding to external signals independently
by regulating their gene expression levels, yet they often locally exchange information
and coordinate. Can such spatial coupling be of benefit for conveying signals
subject to gene regulatory noise? Here we extend our information-theoretic framework
for gene regulation to spatially extended systems. As an example, we consider
a lattice of nuclei responding to a concentration field of a transcriptional regulator
(the "input") by expressing a single diffusible target gene. When input
concentrations are low, diffusive coupling markedly improves information transmission;
optimal gene activation functions also systematically change. A qualitatively
new regulatory strategy emerges where individual cells respond to the input in
a nearly step-like fashion that is subsequently averaged out by strong diffusion.
While motivated by early patterning events in the Drosophila embryo, our framework
is generically applicable to spatially coupled stochastic gene expression models.
article_number: '062710'
author:
- first_name: Thomas R
full_name: Sokolowski, Thomas R
id: 3E999752-F248-11E8-B48F-1D18A9856A87
last_name: Sokolowski
orcid: 0000-0002-1287-3779
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Sokolowski TR, Tkačik G. Optimizing information flow in small genetic networks.
IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter
Physics. 2015;91(6). doi:10.1103/PhysRevE.91.062710
apa: Sokolowski, T. R., & Tkačik, G. (2015). Optimizing information flow in
small genetic networks. IV. Spatial coupling. Physical Review E Statistical
Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.91.062710
chicago: Sokolowski, Thomas R, and Gašper Tkačik. “Optimizing Information Flow in
Small Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical
Nonlinear and Soft Matter Physics. American Institute of Physics, 2015. https://doi.org/10.1103/PhysRevE.91.062710.
ieee: T. R. Sokolowski and G. Tkačik, “Optimizing information flow in small genetic
networks. IV. Spatial coupling,” Physical Review E Statistical Nonlinear and
Soft Matter Physics, vol. 91, no. 6. American Institute of Physics, 2015.
ista: Sokolowski TR, Tkačik G. 2015. Optimizing information flow in small genetic
networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft
Matter Physics. 91(6), 062710.
mla: Sokolowski, Thomas R., and Gašper Tkačik. “Optimizing Information Flow in Small
Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical Nonlinear
and Soft Matter Physics, vol. 91, no. 6, 062710, American Institute of Physics,
2015, doi:10.1103/PhysRevE.91.062710.
short: T.R. Sokolowski, G. Tkačik, Physical Review E Statistical Nonlinear and Soft
Matter Physics 91 (2015).
date_created: 2018-12-11T11:54:49Z
date_published: 2015-06-15T00:00:00Z
date_updated: 2021-01-12T06:54:13Z
day: '15'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.91.062710
intvolume: ' 91'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1501.04015
month: '06'
oa: 1
oa_version: Preprint
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '5145'
quality_controlled: '1'
scopus_import: 1
status: public
title: Optimizing information flow in small genetic networks. IV. Spatial coupling
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 91
year: '2015'
...
---
_id: '9718'
article_processing_charge: No
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Avraham E.
full_name: Mayo, Avraham E.
last_name: Mayo
- first_name: Tsvi
full_name: Tlusty, Tsvi
last_name: Tlusty
- first_name: Uri
full_name: Alon, Uri
last_name: Alon
citation:
ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Supporting information text. 2015.
doi:10.1371/journal.pcbi.1004055.s001
apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Supporting
information text. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s001
chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Supporting
Information Text.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s001.
ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Supporting information
text.” Public Library of Science, 2015.
ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Supporting information text,
Public Library of Science, 10.1371/journal.pcbi.1004055.s001.
mla: Friedlander, Tamar, et al. Supporting Information Text. Public Library
of Science, 2015, doi:10.1371/journal.pcbi.1004055.s001.
short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015).
date_created: 2021-07-26T08:35:23Z
date_published: 2015-03-23T00:00:00Z
date_updated: 2023-02-23T10:16:13Z
day: '23'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1004055.s001
month: '03'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1827'
relation: used_in_publication
status: public
status: public
title: Supporting information text
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2015'
...
---
_id: '1827'
abstract:
- lang: eng
text: Bow-tie or hourglass structure is a common architectural feature found in
many biological systems. A bow-tie in a multi-layered structure occurs when intermediate
layers have much fewer components than the input and output layers. Examples include
metabolism where a handful of building blocks mediate between multiple input nutrients
and multiple output biomass components, and signaling networks where information
from numerous receptor types passes through a small set of signaling pathways
to regulate multiple output genes. Little is known, however, about how bow-tie
architectures evolve. Here, we address the evolution of bow-tie architectures
using simulations of multi-layered systems evolving to fulfill a given input-output
goal. We find that bow-ties spontaneously evolve when the information in the evolutionary
goal can be compressed. Mathematically speaking, bow-ties evolve when the rank
of the input-output matrix describing the evolutionary goal is deficient. The
maximal compression possible (the rank of the goal) determines the size of the
narrowest part of the network—that is the bow-tie. A further requirement is that
a process is active to reduce the number of links in the network, such as product-rule
mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations.
This offers a mechanism to understand a common architectural principle of biological
systems, and a way to quantitate the effective rank of the goals under which they
evolved.
article_processing_charge: No
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Avraham
full_name: Mayo, Avraham
last_name: Mayo
- first_name: Tsvi
full_name: Tlusty, Tsvi
last_name: Tlusty
- first_name: Uri
full_name: Alon, Uri
last_name: Alon
citation:
ama: Friedlander T, Mayo A, Tlusty T, Alon U. Evolution of bow-tie architectures
in biology. PLoS Computational Biology. 2015;11(3). doi:10.1371/journal.pcbi.1004055
apa: Friedlander, T., Mayo, A., Tlusty, T., & Alon, U. (2015). Evolution of
bow-tie architectures in biology. PLoS Computational Biology. Public Library
of Science. https://doi.org/10.1371/journal.pcbi.1004055
chicago: Friedlander, Tamar, Avraham Mayo, Tsvi Tlusty, and Uri Alon. “Evolution
of Bow-Tie Architectures in Biology.” PLoS Computational Biology. Public
Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.
ieee: T. Friedlander, A. Mayo, T. Tlusty, and U. Alon, “Evolution of bow-tie architectures
in biology,” PLoS Computational Biology, vol. 11, no. 3. Public Library
of Science, 2015.
ista: Friedlander T, Mayo A, Tlusty T, Alon U. 2015. Evolution of bow-tie architectures
in biology. PLoS Computational Biology. 11(3).
mla: Friedlander, Tamar, et al. “Evolution of Bow-Tie Architectures in Biology.”
PLoS Computational Biology, vol. 11, no. 3, Public Library of Science,
2015, doi:10.1371/journal.pcbi.1004055.
short: T. Friedlander, A. Mayo, T. Tlusty, U. Alon, PLoS Computational Biology 11
(2015).
date_created: 2018-12-11T11:54:14Z
date_published: 2015-03-23T00:00:00Z
date_updated: 2023-02-23T14:07:51Z
day: '23'
ddc:
- '576'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1004055
ec_funded: 1
file:
- access_level: open_access
checksum: b8aa66f450ff8de393014b87ec7d2efb
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:15:39Z
date_updated: 2020-07-14T12:45:17Z
file_id: '5161'
file_name: IST-2016-452-v1+1_journal.pcbi.1004055.pdf
file_size: 1811647
relation: main_file
file_date_updated: 2020-07-14T12:45:17Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '5278'
pubrep_id: '452'
quality_controlled: '1'
related_material:
record:
- id: '9718'
relation: research_data
status: public
- id: '9773'
relation: research_data
status: public
scopus_import: 1
status: public
title: Evolution of bow-tie architectures in biology
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2015'
...
---
_id: '9773'
article_processing_charge: No
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Avraham E.
full_name: Mayo, Avraham E.
last_name: Mayo
- first_name: Tsvi
full_name: Tlusty, Tsvi
last_name: Tlusty
- first_name: Uri
full_name: Alon, Uri
last_name: Alon
citation:
ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Evolutionary simulation code. 2015.
doi:10.1371/journal.pcbi.1004055.s002
apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Evolutionary
simulation code. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s002
chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Evolutionary
Simulation Code.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s002.
ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Evolutionary simulation
code.” Public Library of Science, 2015.
ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Evolutionary simulation code,
Public Library of Science, 10.1371/journal.pcbi.1004055.s002.
mla: Friedlander, Tamar, et al. Evolutionary Simulation Code. Public Library
of Science, 2015, doi:10.1371/journal.pcbi.1004055.s002.
short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015).
date_created: 2021-08-05T12:58:07Z
date_published: 2015-03-23T00:00:00Z
date_updated: 2023-02-23T10:16:13Z
day: '23'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1004055.s002
month: '03'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1827'
relation: used_in_publication
status: public
status: public
title: Evolutionary simulation code
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2015'
...
---
_id: '9712'
article_processing_charge: No
author:
- first_name: Murat
full_name: Tugrul, Murat
id: 37C323C6-F248-11E8-B48F-1D18A9856A87
last_name: Tugrul
orcid: 0000-0002-8523-0758
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Tugrul M, Paixao T, Barton NH, Tkačik G. Other fitness models for comparison
& for interacting TFBSs. 2015. doi:10.1371/journal.pgen.1005639.s001
apa: Tugrul, M., Paixao, T., Barton, N. H., & Tkačik, G. (2015). Other fitness
models for comparison & for interacting TFBSs. Public Library of Science.
https://doi.org/10.1371/journal.pgen.1005639.s001
chicago: Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Other
Fitness Models for Comparison & for Interacting TFBSs.” Public Library of
Science, 2015. https://doi.org/10.1371/journal.pgen.1005639.s001.
ieee: M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Other fitness models for
comparison & for interacting TFBSs.” Public Library of Science, 2015.
ista: Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Other fitness models for comparison
& for interacting TFBSs, Public Library of Science, 10.1371/journal.pgen.1005639.s001.
mla: Tugrul, Murat, et al. Other Fitness Models for Comparison & for Interacting
TFBSs. Public Library of Science, 2015, doi:10.1371/journal.pgen.1005639.s001.
short: M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, (2015).
date_created: 2021-07-23T12:00:37Z
date_published: 2015-11-06T00:00:00Z
date_updated: 2023-02-23T10:09:08Z
day: '06'
department:
- _id: NiBa
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pgen.1005639.s001
month: '11'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1666'
relation: used_in_publication
status: public
status: public
title: Other fitness models for comparison & for interacting TFBSs
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2015'
...
---
_id: '1666'
abstract:
- lang: eng
text: Evolution of gene regulation is crucial for our understanding of the phenotypic
differences between species, populations and individuals. Sequence-specific binding
of transcription factors to the regulatory regions on the DNA is a key regulatory
mechanism that determines gene expression and hence heritable phenotypic variation.
We use a biophysical model for directional selection on gene expression to estimate
the rates of gain and loss of transcription factor binding sites (TFBS) in finite
populations under both point and insertion/deletion mutations. Our results show
that these rates are typically slow for a single TFBS in an isolated DNA region,
unless the selection is extremely strong. These rates decrease drastically with
increasing TFBS length or increasingly specific protein-DNA interactions, making
the evolution of sites longer than ∼ 10 bp unlikely on typical eukaryotic speciation
timescales. Similarly, evolution converges to the stationary distribution of binding
sequences very slowly, making the equilibrium assumption questionable. The availability
of longer regulatory sequences in which multiple binding sites can evolve simultaneously,
the presence of “pre-sites” or partially decayed old sites in the initial sequence,
and biophysical cooperativity between transcription factors, can all facilitate
gain of TFBS and reconcile theoretical calculations with timescales inferred from
comparative genomics.
author:
- first_name: Murat
full_name: Tugrul, Murat
id: 37C323C6-F248-11E8-B48F-1D18A9856A87
last_name: Tugrul
orcid: 0000-0002-8523-0758
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Tugrul M, Paixao T, Barton NH, Tkačik G. Dynamics of transcription factor binding
site evolution. PLoS Genetics. 2015;11(11). doi:10.1371/journal.pgen.1005639
apa: Tugrul, M., Paixao, T., Barton, N. H., & Tkačik, G. (2015). Dynamics of
transcription factor binding site evolution. PLoS Genetics. Public Library
of Science. https://doi.org/10.1371/journal.pgen.1005639
chicago: Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Dynamics
of Transcription Factor Binding Site Evolution.” PLoS Genetics. Public
Library of Science, 2015. https://doi.org/10.1371/journal.pgen.1005639.
ieee: M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Dynamics of transcription
factor binding site evolution,” PLoS Genetics, vol. 11, no. 11. Public
Library of Science, 2015.
ista: Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Dynamics of transcription factor
binding site evolution. PLoS Genetics. 11(11).
mla: Tugrul, Murat, et al. “Dynamics of Transcription Factor Binding Site Evolution.”
PLoS Genetics, vol. 11, no. 11, Public Library of Science, 2015, doi:10.1371/journal.pgen.1005639.
short: M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, PLoS Genetics 11 (2015).
date_created: 2018-12-11T11:53:21Z
date_published: 2015-11-06T00:00:00Z
date_updated: 2023-09-07T11:53:49Z
day: '06'
ddc:
- '576'
department:
- _id: NiBa
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pgen.1005639
ec_funded: 1
file:
- access_level: open_access
checksum: a4e72fca5ccf40ddacf4d08c8e46b554
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:07:58Z
date_updated: 2020-07-14T12:45:10Z
file_id: '4657'
file_name: IST-2016-463-v1+1_journal.pgen.1005639.pdf
file_size: 2580778
relation: main_file
file_date_updated: 2020-07-14T12:45:10Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '11'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
publication: PLoS Genetics
publication_status: published
publisher: Public Library of Science
publist_id: '5483'
pubrep_id: '463'
quality_controlled: '1'
related_material:
record:
- id: '9712'
relation: research_data
status: public
- id: '1131'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Dynamics of transcription factor binding site evolution
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2015'
...
---
_id: '1576'
abstract:
- lang: eng
text: 'Gene expression is controlled primarily by interactions between transcription
factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured
well by thermodynamic models of regulation. These models, however, neglect regulatory
crosstalk: the possibility that noncognate TFs could initiate transcription, with
potentially disastrous effects for the cell. Here, we estimate the importance
of crosstalk, suggest that its avoidance strongly constrains equilibrium models
of TF binding, and propose an alternative nonequilibrium scheme that implements
kinetic proofreading to suppress erroneous initiation. This proposal is consistent
with the observed covalent modifications of the transcriptional apparatus and
predicts increased noise in gene expression as a trade-off for improved specificity.
Using information theory, we quantify this trade-off to find when optimal proofreading
architectures are favored over their equilibrium counterparts. Such architectures
exhibit significant super-Poisson noise at low expression in steady state.'
article_number: '248101'
author:
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Cepeda Humerez SA, Rieckh G, Tkačik G. Stochastic proofreading mechanism alleviates
crosstalk in transcriptional regulation. Physical Review Letters. 2015;115(24).
doi:10.1103/PhysRevLett.115.248101
apa: Cepeda Humerez, S. A., Rieckh, G., & Tkačik, G. (2015). Stochastic proofreading
mechanism alleviates crosstalk in transcriptional regulation. Physical Review
Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.115.248101
chicago: Cepeda Humerez, Sarah A, Georg Rieckh, and Gašper Tkačik. “Stochastic Proofreading
Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review
Letters. American Physical Society, 2015. https://doi.org/10.1103/PhysRevLett.115.248101.
ieee: S. A. Cepeda Humerez, G. Rieckh, and G. Tkačik, “Stochastic proofreading mechanism
alleviates crosstalk in transcriptional regulation,” Physical Review Letters,
vol. 115, no. 24. American Physical Society, 2015.
ista: Cepeda Humerez SA, Rieckh G, Tkačik G. 2015. Stochastic proofreading mechanism
alleviates crosstalk in transcriptional regulation. Physical Review Letters. 115(24),
248101.
mla: Cepeda Humerez, Sarah A., et al. “Stochastic Proofreading Mechanism Alleviates
Crosstalk in Transcriptional Regulation.” Physical Review Letters, vol.
115, no. 24, 248101, American Physical Society, 2015, doi:10.1103/PhysRevLett.115.248101.
short: S.A. Cepeda Humerez, G. Rieckh, G. Tkačik, Physical Review Letters 115 (2015).
date_created: 2018-12-11T11:52:49Z
date_published: 2015-12-08T00:00:00Z
date_updated: 2023-09-07T12:55:21Z
day: '08'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.115.248101
ec_funded: 1
intvolume: ' 115'
issue: '24'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1504.05716
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '5595'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: 1
status: public
title: Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 115
year: '2015'
...
---
_id: '1655'
abstract:
- lang: eng
text: Quantifying behaviors of robots which were generated autonomously from task-independent
objective functions is an important prerequisite for objective comparisons of
algorithms and movements of animals. The temporal sequence of such a behavior
can be considered as a time series and hence complexity measures developed for
time series are natural candidates for its quantification. The predictive information
and the excess entropy are such complexity measures. They measure the amount of
information the past contains about the future and thus quantify the nonrandom
structure in the temporal sequence. However, when using these measures for systems
with continuous states one has to deal with the fact that their values will depend
on the resolution with which the systems states are observed. For deterministic
systems both measures will diverge with increasing resolution. We therefore propose
a new decomposition of the excess entropy in resolution dependent and resolution
independent parts and discuss how they depend on the dimensionality of the dynamics,
correlations and the noise level. For the practical estimation we propose to use
estimates based on the correlation integral instead of the direct estimation of
the mutual information based on next neighbor statistics because the latter allows
less control of the scale dependencies. Using our algorithm we are able to show
how autonomous learning generates behavior of increasing complexity with increasing
learning duration.
acknowledgement: This work was supported by the DFG priority program 1527 (Autonomous
Learning) and by the European Community’s Seventh Framework Programme (FP7/2007-2013)
under grant agreement no. 318723 (MatheMACS) and from the People Programme (Marie
Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013)
under REA grant agreement no. 291734.
article_processing_charge: No
author:
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
- first_name: Eckehard
full_name: Olbrich, Eckehard
last_name: Olbrich
citation:
ama: Martius GS, Olbrich E. Quantifying emergent behavior of autonomous robots.
Entropy. 2015;17(10):7266-7297. doi:10.3390/e17107266
apa: Martius, G. S., & Olbrich, E. (2015). Quantifying emergent behavior of
autonomous robots. Entropy. MDPI. https://doi.org/10.3390/e17107266
chicago: Martius, Georg S, and Eckehard Olbrich. “Quantifying Emergent Behavior
of Autonomous Robots.” Entropy. MDPI, 2015. https://doi.org/10.3390/e17107266.
ieee: G. S. Martius and E. Olbrich, “Quantifying emergent behavior of autonomous
robots,” Entropy, vol. 17, no. 10. MDPI, pp. 7266–7297, 2015.
ista: Martius GS, Olbrich E. 2015. Quantifying emergent behavior of autonomous robots.
Entropy. 17(10), 7266–7297.
mla: Martius, Georg S., and Eckehard Olbrich. “Quantifying Emergent Behavior of
Autonomous Robots.” Entropy, vol. 17, no. 10, MDPI, 2015, pp. 7266–97,
doi:10.3390/e17107266.
short: G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297.
date_created: 2018-12-11T11:53:17Z
date_published: 2015-10-23T00:00:00Z
date_updated: 2023-10-17T11:42:00Z
day: '23'
ddc:
- '000'
department:
- _id: ChLa
- _id: GaTk
doi: 10.3390/e17107266
ec_funded: 1
file:
- access_level: open_access
checksum: 945d99631a96e0315acb26dc8541dcf9
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:25Z
date_updated: 2020-07-14T12:45:08Z
file_id: '4943'
file_name: IST-2016-464-v1+1_entropy-17-07266.pdf
file_size: 6455007
relation: main_file
file_date_updated: 2020-07-14T12:45:08Z
has_accepted_license: '1'
intvolume: ' 17'
issue: '10'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 7266 - 7297
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Entropy
publication_status: published
publisher: MDPI
publist_id: '5495'
pubrep_id: '464'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantifying emergent behavior of autonomous robots
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2015'
...
---
_id: '1708'
abstract:
- lang: eng
text: It has been long argued that, because of inherent ambiguity and noise, the
brain needs to represent uncertainty in the form of probability distributions.
The neural encoding of such distributions remains however highly controversial.
Here we present a novel circuit model for representing multidimensional real-valued
distributions using a spike based spatio-temporal code. Our model combines the
computational advantages of the currently competing models for probabilistic codes
and exhibits realistic neural responses along a variety of classic measures. Furthermore,
the model highlights the challenges associated with interpreting neural activity
in relation to behavioral uncertainty and points to alternative population-level
approaches for the experimental validation of distributed representations.
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Sophie
full_name: Denève, Sophie
last_name: Denève
citation:
ama: 'Savin C, Denève S. Spatio-temporal representations of uncertainty in spiking
neural networks. In: Vol 3. Neural Information Processing Systems; 2014:2024-2032.'
apa: 'Savin, C., & Denève, S. (2014). Spatio-temporal representations of uncertainty
in spiking neural networks (Vol. 3, pp. 2024–2032). Presented at the NIPS: Neural
Information Processing Systems, Montreal, Canada: Neural Information Processing
Systems.'
chicago: Savin, Cristina, and Sophie Denève. “Spatio-Temporal Representations of
Uncertainty in Spiking Neural Networks,” 3:2024–32. Neural Information Processing
Systems, 2014.
ieee: 'C. Savin and S. Denève, “Spatio-temporal representations of uncertainty in
spiking neural networks,” presented at the NIPS: Neural Information Processing
Systems, Montreal, Canada, 2014, vol. 3, no. January, pp. 2024–2032.'
ista: 'Savin C, Denève S. 2014. Spatio-temporal representations of uncertainty in
spiking neural networks. NIPS: Neural Information Processing Systems vol. 3, 2024–2032.'
mla: Savin, Cristina, and Sophie Denève. Spatio-Temporal Representations of Uncertainty
in Spiking Neural Networks. Vol. 3, no. January, Neural Information Processing
Systems, 2014, pp. 2024–32.
short: C. Savin, S. Denève, in:, Neural Information Processing Systems, 2014, pp.
2024–2032.
conference:
end_date: 2014-12-13
location: Montreal, Canada
name: 'NIPS: Neural Information Processing Systems'
start_date: 2014-12-08
date_created: 2018-12-11T11:53:35Z
date_published: 2014-01-01T00:00:00Z
date_updated: 2021-01-12T06:52:40Z
day: '01'
department:
- _id: GaTk
intvolume: ' 3'
issue: January
language:
- iso: eng
main_file_link:
- url: http://papers.nips.cc/paper/5343-spatio-temporal-representations-of-uncertainty-in-spiking-neural-networks.pdf
month: '01'
oa_version: None
page: 2024 - 2032
publication_status: published
publisher: Neural Information Processing Systems
publist_id: '5427'
quality_controlled: '1'
scopus_import: 1
status: public
title: Spatio-temporal representations of uncertainty in spiking neural networks
type: conference
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2014'
...
---
_id: '1886'
abstract:
- lang: eng
text: 'Information processing in the sensory periphery is shaped by natural stimulus
statistics. In the periphery, a transmission bottleneck constrains performance;
thus efficient coding implies that natural signal components with a predictably
wider range should be compressed. In a different regime—when sampling limitations
constrain performance—efficient coding implies that more resources should be allocated
to informative features that are more variable. We propose that this regime is
relevant for sensory cortex when it extracts complex features from limited numbers
of sensory samples. To test this prediction, we use central visual processing
as a model: we show that visual sensitivity for local multi-point spatial correlations,
described by dozens of independently-measured parameters, can be quantitatively
predicted from the structure of natural images. This suggests that efficient coding
applies centrally, where it extends to higher-order sensory features and operates
in a regime in which sensitivity increases with feature variability.'
article_number: e03722
author:
- first_name: Ann
full_name: Hermundstad, Ann
last_name: Hermundstad
- first_name: John
full_name: Briguglio, John
last_name: Briguglio
- first_name: Mary
full_name: Conte, Mary
last_name: Conte
- first_name: Jonathan
full_name: Victor, Jonathan
last_name: Victor
- first_name: Vijay
full_name: Balasubramanian, Vijay
last_name: Balasubramanian
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkačik G.
Variance predicts salience in central sensory processing. eLife. 2014;(November).
doi:10.7554/eLife.03722
apa: Hermundstad, A., Briguglio, J., Conte, M., Victor, J., Balasubramanian, V.,
& Tkačik, G. (2014). Variance predicts salience in central sensory processing.
ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.03722
chicago: Hermundstad, Ann, John Briguglio, Mary Conte, Jonathan Victor, Vijay Balasubramanian,
and Gašper Tkačik. “Variance Predicts Salience in Central Sensory Processing.”
ELife. eLife Sciences Publications, 2014. https://doi.org/10.7554/eLife.03722.
ieee: A. Hermundstad, J. Briguglio, M. Conte, J. Victor, V. Balasubramanian, and
G. Tkačik, “Variance predicts salience in central sensory processing,” eLife,
no. November. eLife Sciences Publications, 2014.
ista: Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkačik G.
2014. Variance predicts salience in central sensory processing. eLife. (November),
e03722.
mla: Hermundstad, Ann, et al. “Variance Predicts Salience in Central Sensory Processing.”
ELife, no. November, e03722, eLife Sciences Publications, 2014, doi:10.7554/eLife.03722.
short: A. Hermundstad, J. Briguglio, M. Conte, J. Victor, V. Balasubramanian, G.
Tkačik, ELife (2014).
date_created: 2018-12-11T11:54:32Z
date_published: 2014-11-14T00:00:00Z
date_updated: 2021-01-12T06:53:50Z
day: '14'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.7554/eLife.03722
file:
- access_level: open_access
checksum: 766ac8999ac6e3364f10065a06024b8f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:04Z
date_updated: 2020-07-14T12:45:20Z
file_id: '4922'
file_name: IST-2016-420-v1+1_e03722.full.pdf
file_size: 5117086
relation: main_file
file_date_updated: 2020-07-14T12:45:20Z
has_accepted_license: '1'
issue: November
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: eLife
publication_status: published
publisher: eLife Sciences Publications
publist_id: '5209'
pubrep_id: '420'
quality_controlled: '1'
scopus_import: 1
status: public
title: Variance predicts salience in central sensory processing
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
year: '2014'
...
---
_id: '1896'
abstract:
- lang: eng
text: 'Biopolymer length regulation is a complex process that involves a large number
of biological, chemical, and physical subprocesses acting simultaneously across
multiple spatial and temporal scales. An illustrative example important for genomic
stability is the length regulation of telomeres - nucleoprotein structures at
the ends of linear chromosomes consisting of tandemly repeated DNA sequences and
a specialized set of proteins. Maintenance of telomeres is often facilitated by
the enzyme telomerase but, particularly in telomerase-free systems, the maintenance
of chromosomal termini depends on alternative lengthening of telomeres (ALT) mechanisms
mediated by recombination. Various linear and circular DNA structures were identified
to participate in ALT, however, dynamics of the whole process is still poorly
understood. We propose a chemical kinetics model of ALT with kinetic rates systematically
derived from the biophysics of DNA diffusion and looping. The reaction system
is reduced to a coagulation-fragmentation system by quasi-steady-state approximation.
The detailed treatment of kinetic rates yields explicit formulas for expected
size distributions of telomeres that demonstrate the key role played by the J
factor, a quantitative measure of bending of polymers. The results are in agreement
with experimental data and point out interesting phenomena: an appearance of very
long telomeric circles if the total telomere density exceeds a critical value
(excess mass) and a nonlinear response of the telomere size distributions to the
amount of telomeric DNA in the system. The results can be of general importance
for understanding dynamics of telomeres in telomerase-independent systems as this
mode of telomere maintenance is similar to the situation in tumor cells lacking
telomerase activity. Furthermore, due to its universality, the model may also
serve as a prototype of an interaction between linear and circular DNA structures
in various settings.'
acknowledgement: The work was supported by the VEGA Grant No. 1/0459/13 (R.K. and
K.B.).
article_number: '032701'
article_processing_charge: No
author:
- first_name: Richard
full_name: Kollár, Richard
last_name: Kollár
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Jozef
full_name: Nosek, Jozef
last_name: Nosek
- first_name: Ľubomír
full_name: Tomáška, Ľubomír
last_name: Tomáška
citation:
ama: Kollár R, Bodova K, Nosek J, Tomáška Ľ. Mathematical model of alternative mechanism
of telomere length maintenance. Physical Review E Statistical Nonlinear and
Soft Matter Physics. 2014;89(3). doi:10.1103/PhysRevE.89.032701
apa: Kollár, R., Bodova, K., Nosek, J., & Tomáška, Ľ. (2014). Mathematical model
of alternative mechanism of telomere length maintenance. Physical Review E
Statistical Nonlinear and Soft Matter Physics. American Institute of Physics.
https://doi.org/10.1103/PhysRevE.89.032701
chicago: Kollár, Richard, Katarina Bodova, Jozef Nosek, and Ľubomír Tomáška. “Mathematical
Model of Alternative Mechanism of Telomere Length Maintenance.” Physical Review
E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics,
2014. https://doi.org/10.1103/PhysRevE.89.032701.
ieee: R. Kollár, K. Bodova, J. Nosek, and Ľ. Tomáška, “Mathematical model of alternative
mechanism of telomere length maintenance,” Physical Review E Statistical Nonlinear
and Soft Matter Physics, vol. 89, no. 3. American Institute of Physics, 2014.
ista: Kollár R, Bodova K, Nosek J, Tomáška Ľ. 2014. Mathematical model of alternative
mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear
and Soft Matter Physics. 89(3), 032701.
mla: Kollár, Richard, et al. “Mathematical Model of Alternative Mechanism of Telomere
Length Maintenance.” Physical Review E Statistical Nonlinear and Soft Matter
Physics, vol. 89, no. 3, 032701, American Institute of Physics, 2014, doi:10.1103/PhysRevE.89.032701.
short: R. Kollár, K. Bodova, J. Nosek, Ľ. Tomáška, Physical Review E Statistical
Nonlinear and Soft Matter Physics 89 (2014).
date_created: 2018-12-11T11:54:35Z
date_published: 2014-03-04T00:00:00Z
date_updated: 2022-08-01T10:50:10Z
day: '04'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1103/PhysRevE.89.032701
intvolume: ' 89'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1402.0430
month: '03'
oa: 1
oa_version: Submitted Version
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '5198'
scopus_import: '1'
status: public
title: Mathematical model of alternative mechanism of telomere length maintenance
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 89
year: '2014'
...
---
_id: '1909'
abstract:
- lang: eng
text: 'Summary: Phenotypes are often environmentally dependent, which requires organisms
to track environmental change. The challenge for organisms is to construct phenotypes
using the most accurate environmental cue. Here, we use a quantitative genetic
model of adaptation by additive genetic variance, within- and transgenerational
plasticity via linear reaction norms and indirect genetic effects respectively.
We show how the relative influence on the eventual phenotype of these components
depends on the predictability of environmental change (fast or slow, sinusoidal
or stochastic) and the developmental lag τ between when the environment is perceived
and when selection acts. We then decompose expected mean fitness into three components
(variance load, adaptation and fluctuation load) to study the fitness costs of
within- and transgenerational plasticity. A strongly negative maternal effect
coefficient m minimizes the variance load, but a strongly positive m minimises
the fluctuation load. The adaptation term is maximized closer to zero, with positive
or negative m preferred under different environmental scenarios. Phenotypic plasticity
is higher when τ is shorter and when the environment changes frequently between
seasonal extremes. Expected mean population fitness is highest away from highest
observed levels of phenotypic plasticity. Within- and transgenerational plasticity
act in concert to deliver well-adapted phenotypes, which emphasizes the need to
study both simultaneously when investigating phenotypic evolution.'
acknowledgement: 'Engineering and Physical Sciences Research Council. Grant Number:
EP/H031928/1'
author:
- first_name: Thomas
full_name: Ezard, Thomas
last_name: Ezard
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Rebecca
full_name: Hoyle, Rebecca
last_name: Hoyle
citation:
ama: Ezard T, Prizak R, Hoyle R. The fitness costs of adaptation via phenotypic
plasticity and maternal effects. Functional Ecology. 2014;28(3):693-701.
doi:10.1111/1365-2435.12207
apa: Ezard, T., Prizak, R., & Hoyle, R. (2014). The fitness costs of adaptation
via phenotypic plasticity and maternal effects. Functional Ecology. Wiley-Blackwell.
https://doi.org/10.1111/1365-2435.12207
chicago: Ezard, Thomas, Roshan Prizak, and Rebecca Hoyle. “The Fitness Costs of
Adaptation via Phenotypic Plasticity and Maternal Effects.” Functional Ecology.
Wiley-Blackwell, 2014. https://doi.org/10.1111/1365-2435.12207.
ieee: T. Ezard, R. Prizak, and R. Hoyle, “The fitness costs of adaptation via phenotypic
plasticity and maternal effects,” Functional Ecology, vol. 28, no. 3. Wiley-Blackwell,
pp. 693–701, 2014.
ista: Ezard T, Prizak R, Hoyle R. 2014. The fitness costs of adaptation via phenotypic
plasticity and maternal effects. Functional Ecology. 28(3), 693–701.
mla: Ezard, Thomas, et al. “The Fitness Costs of Adaptation via Phenotypic Plasticity
and Maternal Effects.” Functional Ecology, vol. 28, no. 3, Wiley-Blackwell,
2014, pp. 693–701, doi:10.1111/1365-2435.12207.
short: T. Ezard, R. Prizak, R. Hoyle, Functional Ecology 28 (2014) 693–701.
date_created: 2018-12-11T11:54:40Z
date_published: 2014-06-01T00:00:00Z
date_updated: 2021-01-12T06:54:00Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1111/1365-2435.12207
file:
- access_level: open_access
checksum: 3cbe8623174709a8ceec2103246f8fe0
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:15:45Z
date_updated: 2020-07-14T12:45:20Z
file_id: '5167'
file_name: IST-2016-419-v1+1_Ezard_et_al-2014-Functional_Ecology.pdf
file_size: 536154
relation: main_file
file_date_updated: 2020-07-14T12:45:20Z
has_accepted_license: '1'
intvolume: ' 28'
issue: '3'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 693 - 701
publication: Functional Ecology
publication_status: published
publisher: Wiley-Blackwell
publist_id: '5186'
pubrep_id: '419'
scopus_import: 1
status: public
title: The fitness costs of adaptation via phenotypic plasticity and maternal effects
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 28
year: '2014'
...
---
_id: '1928'
abstract:
- lang: eng
text: In infectious disease epidemiology the basic reproductive ratio, R0, is defined
as the average number of new infections caused by a single infected individual
in a fully susceptible population. Many models describing competition for hosts
between non-interacting pathogen strains in an infinite population lead to the
conclusion that selection favors invasion of new strains if and only if they have
higher R0 values than the resident. Here we demonstrate that this picture fails
in finite populations. Using a simple stochastic SIS model, we show that in general
there is no analogous optimization principle. We find that successive invasions
may in some cases lead to strains that infect a smaller fraction of the host population,
and that mutually invasible pathogen strains exist. In the limit of weak selection
we demonstrate that an optimization principle does exist, although it differs
from R0 maximization. For strains with very large R0, we derive an expression
for this local fitness function and use it to establish a lower bound for the
error caused by neglecting stochastic effects. Furthermore, we apply this weak
selection limit to investigate the selection dynamics in the presence of a trade-off
between the virulence and the transmission rate of a pathogen.
acknowledgement: J.H. received support from the Zdenek Bakala Foundation and the Mobility
Fund of Charles University in Prague.
author:
- first_name: Jan
full_name: Humplik, Jan
id: 2E9627A8-F248-11E8-B48F-1D18A9856A87
last_name: Humplik
- first_name: Alison
full_name: Hill, Alison
last_name: Hill
- first_name: Martin
full_name: Nowak, Martin
last_name: Nowak
citation:
ama: Humplik J, Hill A, Nowak M. Evolutionary dynamics of infectious diseases in
finite populations. Journal of Theoretical Biology. 2014;360:149-162. doi:10.1016/j.jtbi.2014.06.039
apa: Humplik, J., Hill, A., & Nowak, M. (2014). Evolutionary dynamics of infectious
diseases in finite populations. Journal of Theoretical Biology. Elsevier.
https://doi.org/10.1016/j.jtbi.2014.06.039
chicago: Humplik, Jan, Alison Hill, and Martin Nowak. “Evolutionary Dynamics of
Infectious Diseases in Finite Populations.” Journal of Theoretical Biology.
Elsevier, 2014. https://doi.org/10.1016/j.jtbi.2014.06.039.
ieee: J. Humplik, A. Hill, and M. Nowak, “Evolutionary dynamics of infectious diseases
in finite populations,” Journal of Theoretical Biology, vol. 360. Elsevier,
pp. 149–162, 2014.
ista: Humplik J, Hill A, Nowak M. 2014. Evolutionary dynamics of infectious diseases
in finite populations. Journal of Theoretical Biology. 360, 149–162.
mla: Humplik, Jan, et al. “Evolutionary Dynamics of Infectious Diseases in Finite
Populations.” Journal of Theoretical Biology, vol. 360, Elsevier, 2014,
pp. 149–62, doi:10.1016/j.jtbi.2014.06.039.
short: J. Humplik, A. Hill, M. Nowak, Journal of Theoretical Biology 360 (2014)
149–162.
date_created: 2018-12-11T11:54:46Z
date_published: 2014-11-07T00:00:00Z
date_updated: 2021-01-12T06:54:08Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.jtbi.2014.06.039
intvolume: ' 360'
language:
- iso: eng
month: '11'
oa_version: None
page: 149 - 162
publication: Journal of Theoretical Biology
publication_status: published
publisher: Elsevier
publist_id: '5166'
scopus_import: 1
status: public
title: Evolutionary dynamics of infectious diseases in finite populations
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 360
year: '2014'
...
---
_id: '1931'
abstract:
- lang: eng
text: A wealth of experimental evidence suggests that working memory circuits preferentially
represent information that is behaviorally relevant. Still, we are missing a mechanistic
account of how these representations come about. Here we provide a simple explanation
for a range of experimental findings, in light of prefrontal circuits adapting
to task constraints by reward-dependent learning. In particular, we model a neural
network shaped by reward-modulated spike-timing dependent plasticity (r-STDP)
and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show
that the experimentally-observed neural representations naturally emerge in an
initially unstructured circuit as it learns to solve several working memory tasks.
These results point to a critical, and previously unappreciated, role for reward-dependent
learning in shaping prefrontal cortex activity.
acknowledgement: Supported in part by EC MEXT project PLICON and the LOEWE-Program
“Neuronal Coordination Research Focus Frankfurt” (NeFF). Jochen Triesch was supported
by the Quandt foundation.
article_number: '57'
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Jochen
full_name: Triesch, Jochen
last_name: Triesch
citation:
ama: Savin C, Triesch J. Emergence of task-dependent representations in working
memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY).
doi:10.3389/fncom.2014.00057
apa: Savin, C., & Triesch, J. (2014). Emergence of task-dependent representations
in working memory circuits. Frontiers in Computational Neuroscience. Frontiers
Research Foundation. https://doi.org/10.3389/fncom.2014.00057
chicago: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations
in Working Memory Circuits.” Frontiers in Computational Neuroscience. Frontiers
Research Foundation, 2014. https://doi.org/10.3389/fncom.2014.00057.
ieee: C. Savin and J. Triesch, “Emergence of task-dependent representations in working
memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no.
MAY. Frontiers Research Foundation, 2014.
ista: Savin C, Triesch J. 2014. Emergence of task-dependent representations in working
memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57.
mla: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations
in Working Memory Circuits.” Frontiers in Computational Neuroscience, vol.
8, no. MAY, 57, Frontiers Research Foundation, 2014, doi:10.3389/fncom.2014.00057.
short: C. Savin, J. Triesch, Frontiers in Computational Neuroscience 8 (2014).
date_created: 2018-12-11T11:54:46Z
date_published: 2014-05-28T00:00:00Z
date_updated: 2021-01-12T06:54:09Z
day: '28'
department:
- _id: GaTk
doi: 10.3389/fncom.2014.00057
intvolume: ' 8'
issue: MAY
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035833/
month: '05'
oa: 1
oa_version: Submitted Version
publication: Frontiers in Computational Neuroscience
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '5163'
quality_controlled: '1'
scopus_import: 1
status: public
title: Emergence of task-dependent representations in working memory circuits
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2014'
...
---
_id: '2028'
abstract:
- lang: eng
text: 'Understanding the dynamics of noisy neurons remains an important challenge
in neuroscience. Here, we describe a simple probabilistic model that accurately
describes the firing behavior in a large class (type II) of neurons. To demonstrate
the usefulness of this model, we show how it accurately predicts the interspike
interval (ISI) distributions, bursting patterns and mean firing rates found by:
(1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental
data from squid giant axon with a noisy input current and (3) experimental data
on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple
model has 6 parameters, however, in some cases, two of these parameters are coupled
and only 5 parameters account for much of the known behavior. From these parameters,
many properties of spiking can be found through simple calculation. Thus, we show
how the complex effects of noise can be understood through a simple and general
probabilistic model.'
acknowledgement: 'This work is supported by AFOSR grant FA 9550-11-1-0165, program
grant RPG 24/2012 from the Human Frontiers of Science (DBF) and travel support from
the European Commission Marie Curie International Reintegration Grant PIRG04-GA-2008-239429
(KB). DP was supported by NIHR01 GM104987 and the Wyss Institute of Biologically
Inspired Engineering. '
article_processing_charge: No
author:
- first_name: Katarina
full_name: Bodova, Katarina
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bodova
orcid: 0000-0002-7214-0171
- first_name: David
full_name: Paydarfar, David
last_name: Paydarfar
- first_name: Daniel
full_name: Forger, Daniel
last_name: Forger
citation:
ama: Bodova K, Paydarfar D, Forger D. Characterizing spiking in noisy type II neurons.
Journal of Theoretical Biology. 2014;365:40-54. doi:10.1016/j.jtbi.2014.09.041
apa: Bodova, K., Paydarfar, D., & Forger, D. (2014). Characterizing spiking
in noisy type II neurons. Journal of Theoretical Biology. Academic Press.
https://doi.org/10.1016/j.jtbi.2014.09.041
chicago: Bodova, Katarina, David Paydarfar, and Daniel Forger. “Characterizing Spiking
in Noisy Type II Neurons.” Journal of Theoretical Biology. Academic Press,
2014. https://doi.org/10.1016/j.jtbi.2014.09.041.
ieee: K. Bodova, D. Paydarfar, and D. Forger, “Characterizing spiking in noisy type
II neurons,” Journal of Theoretical Biology, vol. 365. Academic Press,
pp. 40–54, 2014.
ista: Bodova K, Paydarfar D, Forger D. 2014. Characterizing spiking in noisy type
II neurons. Journal of Theoretical Biology. 365, 40–54.
mla: Bodova, Katarina, et al. “Characterizing Spiking in Noisy Type II Neurons.”
Journal of Theoretical Biology, vol. 365, Academic Press, 2014, pp. 40–54,
doi:10.1016/j.jtbi.2014.09.041.
short: K. Bodova, D. Paydarfar, D. Forger, Journal of Theoretical Biology 365 (2014)
40–54.
date_created: 2018-12-11T11:55:18Z
date_published: 2014-10-12T00:00:00Z
date_updated: 2022-08-25T14:00:47Z
day: '12'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.jtbi.2014.09.041
file:
- access_level: open_access
checksum: a9dbae18d3233b3dab6944fd3f2cd49e
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:17:58Z
date_updated: 2020-07-14T12:45:25Z
file_id: '5316'
file_name: IST-2016-444-v1+1_1-s2.0-S0022519314005888-main.pdf
file_size: 2679222
relation: main_file
file_date_updated: 2020-07-14T12:45:25Z
has_accepted_license: '1'
intvolume: ' 365'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 40 - 54
publication: ' Journal of Theoretical Biology'
publication_status: published
publisher: Academic Press
publist_id: '5043'
pubrep_id: '444'
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1016/j.jtbi.2015.03.013
scopus_import: '1'
status: public
title: Characterizing spiking in noisy type II neurons
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 365
year: '2014'
...
---
_id: '2183'
abstract:
- lang: eng
text: 'We describe a simple adaptive network of coupled chaotic maps. The network
reaches a stationary state (frozen topology) for all values of the coupling parameter,
although the dynamics of the maps at the nodes of the network can be nontrivial.
The structure of the network shows interesting hierarchical properties and in
certain parameter regions the dynamics is polysynchronous: Nodes can be divided
in differently synchronized classes but, contrary to cluster synchronization,
nodes in the same class need not be connected to each other. These complicated
synchrony patterns have been conjectured to play roles in systems biology and
circuits. The adaptive system we study describes ways whereby this behavior can
evolve from undifferentiated nodes.'
acknowledgement: "V.B.S. is partially supported by contract MEC (Grant No. AYA2010-22111-C03-02).\r\n"
article_number: '062809'
article_processing_charge: No
author:
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Paul
full_name: Glendinning, Paul
last_name: Glendinning
citation:
ama: Botella Soler V, Glendinning P. Hierarchy and polysynchrony in an adaptive
network . Physical Review E Statistical Nonlinear and Soft Matter Physics.
2014;89(6). doi:10.1103/PhysRevE.89.062809
apa: Botella Soler, V., & Glendinning, P. (2014). Hierarchy and polysynchrony
in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter
Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.89.062809
chicago: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony
in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft
Matter Physics. American Institute of Physics, 2014. https://doi.org/10.1103/PhysRevE.89.062809.
ieee: V. Botella Soler and P. Glendinning, “Hierarchy and polysynchrony in an adaptive
network ,” Physical Review E Statistical Nonlinear and Soft Matter Physics,
vol. 89, no. 6. American Institute of Physics, 2014.
ista: Botella Soler V, Glendinning P. 2014. Hierarchy and polysynchrony in an adaptive
network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(6),
062809.
mla: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony
in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft
Matter Physics, vol. 89, no. 6, 062809, American Institute of Physics, 2014,
doi:10.1103/PhysRevE.89.062809.
short: V. Botella Soler, P. Glendinning, Physical Review E Statistical Nonlinear
and Soft Matter Physics 89 (2014).
date_created: 2018-12-11T11:56:11Z
date_published: 2014-06-16T00:00:00Z
date_updated: 2022-08-25T14:04:45Z
day: '16'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.89.062809
ec_funded: 1
intvolume: ' 89'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1403.3209
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '4798'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Hierarchy and polysynchrony in an adaptive network '
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 89
year: '2014'
...
---
_id: '2231'
abstract:
- lang: eng
text: Based on the measurements of noise in gene expression performed during the
past decade, it has become customary to think of gene regulation in terms of a
two-state model, where the promoter of a gene can stochastically switch between
an ON and an OFF state. As experiments are becoming increasingly precise and the
deviations from the two-state model start to be observable, we ask about the experimental
signatures of complex multistate promoters, as well as the functional consequences
of this additional complexity. In detail, we i), extend the calculations for noise
in gene expression to promoters described by state transition diagrams with multiple
states, ii), systematically compute the experimentally accessible noise characteristics
for these complex promoters, and iii), use information theory to evaluate the
channel capacities of complex promoter architectures and compare them with the
baseline provided by the two-state model. We find that adding internal states
to the promoter generically decreases channel capacity, except in certain cases,
three of which (cooperativity, dual-role regulation, promoter cycling) we analyze
in detail.
author:
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Rieckh G, Tkačik G. Noise and information transmission in promoters with multiple
internal states. Biophysical Journal. 2014;106(5):1194-1204. doi:10.1016/j.bpj.2014.01.014
apa: Rieckh, G., & Tkačik, G. (2014). Noise and information transmission in
promoters with multiple internal states. Biophysical Journal. Biophysical
Society. https://doi.org/10.1016/j.bpj.2014.01.014
chicago: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in
Promoters with Multiple Internal States.” Biophysical Journal. Biophysical
Society, 2014. https://doi.org/10.1016/j.bpj.2014.01.014.
ieee: G. Rieckh and G. Tkačik, “Noise and information transmission in promoters
with multiple internal states,” Biophysical Journal, vol. 106, no. 5. Biophysical
Society, pp. 1194–1204, 2014.
ista: Rieckh G, Tkačik G. 2014. Noise and information transmission in promoters
with multiple internal states. Biophysical Journal. 106(5), 1194–1204.
mla: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters
with Multiple Internal States.” Biophysical Journal, vol. 106, no. 5, Biophysical
Society, 2014, pp. 1194–204, doi:10.1016/j.bpj.2014.01.014.
short: G. Rieckh, G. Tkačik, Biophysical Journal 106 (2014) 1194–1204.
date_created: 2018-12-11T11:56:28Z
date_published: 2014-03-04T00:00:00Z
date_updated: 2021-01-12T06:56:10Z
day: '04'
department:
- _id: GaTk
doi: 10.1016/j.bpj.2014.01.014
external_id:
pmid:
- '24606943'
intvolume: ' 106'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026790/
month: '03'
oa: 1
oa_version: Submitted Version
page: 1194 - 1204
pmid: 1
publication: Biophysical Journal
publication_identifier:
issn:
- '00063495'
publication_status: published
publisher: Biophysical Society
publist_id: '4730'
quality_controlled: '1'
scopus_import: 1
status: public
title: Noise and information transmission in promoters with multiple internal states
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 106
year: '2014'
...
---
_id: '3263'
abstract:
- lang: eng
text: Adaptation in the retina is thought to optimize the encoding of natural light
signals into sequences of spikes sent to the brain. While adaptive changes in
retinal processing to the variations of the mean luminance level and second-order
stimulus statistics have been documented before, no such measurements have been
performed when higher-order moments of the light distribution change. We therefore
measured the ganglion cell responses in the tiger salamander retina to controlled
changes in the second (contrast), third (skew) and fourth (kurtosis) moments of
the light intensity distribution of spatially uniform temporally independent stimuli.
The skew and kurtosis of the stimuli were chosen to cover the range observed in
natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear
models that capture well the retinal encoding properties across all stimuli. We
found that the encoding properties of retinal ganglion cells change only marginally
when higher-order statistics change, compared to the changes observed in response
to the variation in contrast. By analyzing optimal coding in LN-type models, we
showed that neurons can maintain a high information rate without large dynamic
adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli,
spatio-temporal summation within the receptive field averages away non-gaussian
aspects of the light intensity distribution.
acknowledgement: "This work was supported by The Israel Science Foundation and The
Human Frontiers Science Program.\r\nWe thank the referees for helping significantly
improve this paper. We also thank Vijay Balasubramanian, Kristina Simmons, and Jason
Prentice for stimulating discussions. GT wishes to thank the faculty and students
of the “Methods in Computational Neuroscience” course at Marine Biological Laboratory,
Woods Hole.\r\n"
article_number: e85841
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Anandamohan
full_name: Ghosh, Anandamohan
last_name: Ghosh
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
- first_name: Ronen
full_name: Segev, Ronen
last_name: Segev
citation:
ama: Tkačik G, Ghosh A, Schneidman E, Segev R. Adaptation to changes in higher-order
stimulus statistics in the salamander retina. PLoS One. 2014;9(1). doi:10.1371/journal.pone.0085841
apa: Tkačik, G., Ghosh, A., Schneidman, E., & Segev, R. (2014). Adaptation to
changes in higher-order stimulus statistics in the salamander retina. PLoS
One. Public Library of Science. https://doi.org/10.1371/journal.pone.0085841
chicago: Tkačik, Gašper, Anandamohan Ghosh, Elad Schneidman, and Ronen Segev. “Adaptation
to Changes in Higher-Order Stimulus Statistics in the Salamander Retina.” PLoS
One. Public Library of Science, 2014. https://doi.org/10.1371/journal.pone.0085841.
ieee: G. Tkačik, A. Ghosh, E. Schneidman, and R. Segev, “Adaptation to changes in
higher-order stimulus statistics in the salamander retina,” PLoS One, vol.
9, no. 1. Public Library of Science, 2014.
ista: Tkačik G, Ghosh A, Schneidman E, Segev R. 2014. Adaptation to changes in higher-order
stimulus statistics in the salamander retina. PLoS One. 9(1), e85841.
mla: Tkačik, Gašper, et al. “Adaptation to Changes in Higher-Order Stimulus Statistics
in the Salamander Retina.” PLoS One, vol. 9, no. 1, e85841, Public Library
of Science, 2014, doi:10.1371/journal.pone.0085841.
short: G. Tkačik, A. Ghosh, E. Schneidman, R. Segev, PLoS One 9 (2014).
date_created: 2018-12-11T12:02:20Z
date_published: 2014-01-21T00:00:00Z
date_updated: 2021-01-12T07:42:14Z
day: '21'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0085841
file:
- access_level: open_access
checksum: 1d5816b343abe5eadc3eb419bcece971
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:28Z
date_updated: 2020-07-14T12:46:06Z
file_id: '5011'
file_name: IST-2016-432-v1+1_journal.pone.0085841.pdf
file_size: 1568524
relation: main_file
file_date_updated: 2020-07-14T12:46:06Z
has_accepted_license: '1'
intvolume: ' 9'
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '3385'
pubrep_id: '432'
quality_controlled: '1'
scopus_import: 1
status: public
title: Adaptation to changes in higher-order stimulus statistics in the salamander
retina
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3FFCCD3A-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2014'
...
---
_id: '537'
abstract:
- lang: eng
text: Transgenerational effects are broader than only parental relationships. Despite
mounting evidence that multigenerational effects alter phenotypic and life-history
traits, our understanding of how they combine to determine fitness is not well
developed because of the added complexity necessary to study them. Here, we derive
a quantitative genetic model of adaptation to an extraordinary new environment
by an additive genetic component, phenotypic plasticity, maternal and grandmaternal
effects. We show how, at equilibrium, negative maternal and negative grandmaternal
effects maximize expected population mean fitness. We define negative transgenerational
effects as those that have a negative effect on trait expression in the subsequent
generation, that is, they slow, or potentially reverse, the expected evolutionary
dynamic. When maternal effects are positive, negative grandmaternal effects are
preferred. As expected under Mendelian inheritance, the grandmaternal effects
have a lower impact on fitness than the maternal effects, but this dual inheritance
model predicts a more complex relationship between maternal and grandmaternal
effects to constrain phenotypic variance and so maximize expected population mean
fitness in the offspring.
author:
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Thomas
full_name: Ezard, Thomas
last_name: Ezard
- first_name: Rebecca
full_name: Hoyle, Rebecca
last_name: Hoyle
citation:
ama: Prizak R, Ezard T, Hoyle R. Fitness consequences of maternal and grandmaternal
effects. Ecology and Evolution. 2014;4(15):3139-3145. doi:10.1002/ece3.1150
apa: Prizak, R., Ezard, T., & Hoyle, R. (2014). Fitness consequences of maternal
and grandmaternal effects. Ecology and Evolution. Wiley-Blackwell. https://doi.org/10.1002/ece3.1150
chicago: Prizak, Roshan, Thomas Ezard, and Rebecca Hoyle. “Fitness Consequences
of Maternal and Grandmaternal Effects.” Ecology and Evolution. Wiley-Blackwell,
2014. https://doi.org/10.1002/ece3.1150.
ieee: R. Prizak, T. Ezard, and R. Hoyle, “Fitness consequences of maternal and grandmaternal
effects,” Ecology and Evolution, vol. 4, no. 15. Wiley-Blackwell, pp. 3139–3145,
2014.
ista: Prizak R, Ezard T, Hoyle R. 2014. Fitness consequences of maternal and grandmaternal
effects. Ecology and Evolution. 4(15), 3139–3145.
mla: Prizak, Roshan, et al. “Fitness Consequences of Maternal and Grandmaternal
Effects.” Ecology and Evolution, vol. 4, no. 15, Wiley-Blackwell, 2014,
pp. 3139–45, doi:10.1002/ece3.1150.
short: R. Prizak, T. Ezard, R. Hoyle, Ecology and Evolution 4 (2014) 3139–3145.
date_created: 2018-12-11T11:47:02Z
date_published: 2014-07-19T00:00:00Z
date_updated: 2021-01-12T08:01:30Z
day: '19'
ddc:
- '530'
- '571'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1002/ece3.1150
file:
- access_level: open_access
checksum: e32abf75a248e7a11811fd7f60858769
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:31Z
date_updated: 2020-07-14T12:46:38Z
file_id: '4886'
file_name: IST-2018-934-v1+1_Prizak_et_al-2014-Ecology_and_Evolution.pdf
file_size: 621582
relation: main_file
file_date_updated: 2020-07-14T12:46:38Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '15'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 3139 - 3145
publication: Ecology and Evolution
publication_status: published
publisher: Wiley-Blackwell
publist_id: '7280'
pubrep_id: '934'
scopus_import: 1
status: public
title: Fitness consequences of maternal and grandmaternal effects
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2014'
...
---
_id: '9752'
abstract:
- lang: eng
text: Redundancies and correlations in the responses of sensory neurons may seem
to waste neural resources, but they can also carry cues about structured stimuli
and may help the brain to correct for response errors. To investigate the effect
of stimulus structure on redundancy in retina, we measured simultaneous responses
from populations of retinal ganglion cells presented with natural and artificial
stimuli that varied greatly in correlation structure; these stimuli and recordings
are publicly available online. Responding to spatio-temporally structured stimuli
such as natural movies, pairs of ganglion cells were modestly more correlated
than in response to white noise checkerboards, but they were much less correlated
than predicted by a non-adapting functional model of retinal response. Meanwhile,
responding to stimuli with purely spatial correlations, pairs of ganglion cells
showed increased correlations consistent with a static, non-adapting receptive
field and nonlinearity. We found that in response to spatio-temporally correlated
stimuli, ganglion cells had faster temporal kernels and tended to have stronger
surrounds. These properties of individual cells, along with gain changes that
opposed changes in effective contrast at the ganglion cell input, largely explained
the pattern of pairwise correlations across stimuli where receptive field measurements
were possible.
article_processing_charge: No
author:
- first_name: Kristina
full_name: Simmons, Kristina
last_name: Simmons
- first_name: Jason
full_name: Prentice, Jason
last_name: Prentice
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Jan
full_name: Homann, Jan
last_name: Homann
- first_name: Heather
full_name: Yee, Heather
last_name: Yee
- first_name: Stephanie
full_name: Palmer, Stephanie
last_name: Palmer
- first_name: Philip
full_name: Nelson, Philip
last_name: Nelson
- first_name: Vijay
full_name: Balasubramanian, Vijay
last_name: Balasubramanian
citation:
ama: 'Simmons K, Prentice J, Tkačik G, et al. Data from: Transformation of stimulus
correlations by the retina. 2014. doi:10.5061/dryad.246qg'
apa: 'Simmons, K., Prentice, J., Tkačik, G., Homann, J., Yee, H., Palmer, S., …
Balasubramanian, V. (2014). Data from: Transformation of stimulus correlations
by the retina. Dryad. https://doi.org/10.5061/dryad.246qg'
chicago: 'Simmons, Kristina, Jason Prentice, Gašper Tkačik, Jan Homann, Heather
Yee, Stephanie Palmer, Philip Nelson, and Vijay Balasubramanian. “Data from: Transformation
of Stimulus Correlations by the Retina.” Dryad, 2014. https://doi.org/10.5061/dryad.246qg.'
ieee: 'K. Simmons et al., “Data from: Transformation of stimulus correlations
by the retina.” Dryad, 2014.'
ista: 'Simmons K, Prentice J, Tkačik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian
V. 2014. Data from: Transformation of stimulus correlations by the retina, Dryad,
10.5061/dryad.246qg.'
mla: 'Simmons, Kristina, et al. Data from: Transformation of Stimulus Correlations
by the Retina. Dryad, 2014, doi:10.5061/dryad.246qg.'
short: K. Simmons, J. Prentice, G. Tkačik, J. Homann, H. Yee, S. Palmer, P. Nelson,
V. Balasubramanian, (2014).
date_created: 2021-07-30T08:13:52Z
date_published: 2014-11-07T00:00:00Z
date_updated: 2023-02-23T10:35:57Z
day: '07'
department:
- _id: GaTk
doi: 10.5061/dryad.246qg
main_file_link:
- open_access: '1'
url: https://doi.org/10.5061/dryad.246qg
month: '11'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
record:
- id: '2277'
relation: used_in_publication
status: public
status: public
title: 'Data from: Transformation of stimulus correlations by the retina'
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2014'
...
---
_id: '2257'
abstract:
- lang: eng
text: 'Maximum entropy models are the least structured probability distributions
that exactly reproduce a chosen set of statistics measured in an interacting network.
Here we use this principle to construct probabilistic models which describe the
correlated spiking activity of populations of up to 120 neurons in the salamander
retina as it responds to natural movies. Already in groups as small as 10 neurons,
interactions between spikes can no longer be regarded as small perturbations in
an otherwise independent system; for 40 or more neurons pairwise interactions
need to be supplemented by a global interaction that controls the distribution
of synchrony in the population. Here we show that such “K-pairwise” models—being
systematic extensions of the previously used pairwise Ising models—provide an
excellent account of the data. We explore the properties of the neural vocabulary
by: 1) estimating its entropy, which constrains the population''s capacity to
represent visual information; 2) classifying activity patterns into a small set
of metastable collective modes; 3) showing that the neural codeword ensembles
are extremely inhomogenous; 4) demonstrating that the state of individual neurons
is highly predictable from the rest of the population, allowing the capacity for
error correction.'
acknowledgement: "\r\n\r\n\r\n\r\nThis work was funded by NSF grant IIS-0613435, NSF
grant PHY-0957573, NSF grant CCF-0939370, NIH grant R01 EY14196, NIH grant P50 GM071508,
the Fannie and John Hertz Foundation, the Swartz Foundation, the WM Keck Foundation,
ANR Optima and the French State program “Investissements d'Avenir” [LIFESENSES:
ANR-10-LABX-65], and the Austrian Research Foundation FWF P25651."
article_number: e1003408
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Dario
full_name: Amodei, Dario
last_name: Amodei
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
- first_name: William
full_name: Bialek, William
last_name: Bialek
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
citation:
ama: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. Searching for
collective behavior in a large network of sensory neurons. PLoS Computational
Biology. 2014;10(1). doi:10.1371/journal.pcbi.1003408
apa: Tkačik, G., Marre, O., Amodei, D., Schneidman, E., Bialek, W., & Berry,
M. (2014). Searching for collective behavior in a large network of sensory neurons.
PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1003408
chicago: Tkačik, Gašper, Olivier Marre, Dario Amodei, Elad Schneidman, William Bialek,
and Michael Berry. “Searching for Collective Behavior in a Large Network of Sensory
Neurons.” PLoS Computational Biology. Public Library of Science, 2014.
https://doi.org/10.1371/journal.pcbi.1003408.
ieee: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Searching
for collective behavior in a large network of sensory neurons,” PLoS Computational
Biology, vol. 10, no. 1. Public Library of Science, 2014.
ista: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. 2014. Searching
for collective behavior in a large network of sensory neurons. PLoS Computational
Biology. 10(1), e1003408.
mla: Tkačik, Gašper, et al. “Searching for Collective Behavior in a Large Network
of Sensory Neurons.” PLoS Computational Biology, vol. 10, no. 1, e1003408,
Public Library of Science, 2014, doi:10.1371/journal.pcbi.1003408.
short: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, M. Berry, PLoS
Computational Biology 10 (2014).
date_created: 2018-12-11T11:56:36Z
date_published: 2014-01-02T00:00:00Z
date_updated: 2024-02-21T13:46:14Z
day: '02'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1003408
file:
- access_level: open_access
checksum: c720222c5e924a4acb17f23b9381a6ca
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:46Z
date_updated: 2020-07-14T12:45:35Z
file_id: '4965'
file_name: IST-2016-436-v1+1_journal.pcbi.1003408.pdf
file_size: 2194790
relation: main_file
file_date_updated: 2020-07-14T12:45:35Z
has_accepted_license: '1'
intvolume: ' 10'
issue: '1'
language:
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main_file_link:
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url: http://repository.ist.ac.at/id/eprint/436
month: '01'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '4689'
pubrep_id: '436'
quality_controlled: '1'
related_material:
record:
- id: '5562'
relation: popular_science
status: public
scopus_import: 1
status: public
title: Searching for collective behavior in a large network of sensory neurons
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 10
year: '2014'
...
---
_id: '2413'
abstract:
- lang: eng
text: 'Progress in understanding the global brain dynamics has remained slow to
date in large part because of the highly multiscale nature of brain activity.
Indeed, normal brain dynamics is characterized by complex interactions between
multiple levels: from the microscopic scale of single neurons to the mesoscopic
level of local groups of neurons, and finally to the macroscopic level of the
whole brain. Among the most difficult tasks are those of identifying which scales
are significant for a given particular function and describing how the scales
affect each other. It is important to realize that the scales of time and space
are linked together, or even intertwined, and that causal inference is far more
ambiguous between than within levels. We approach this problem from the perspective
of our recent work on simultaneous recording from micro- and macroelectrodes in
the human brain. We propose a physiological description of these multilevel interactions,
based on phase–amplitude coupling of neuronal oscillations that operate at multiple
frequencies and on different spatial scales. Specifically, the amplitude of the
oscillations on a particular spatial scale is modulated by phasic variations in
neuronal excitability induced by lower frequency oscillations that emerge on a
larger spatial scale. Following this general principle, it is possible to scale
up or scale down the multiscale brain dynamics. It is expected that large-scale
network oscillations in the low-frequency range, mediating downward effects, may
play an important role in attention and consciousness.'
alternative_title:
- Reviews of Nonlinear Dynamics and Complexity
author:
- first_name: Mario
full_name: Valderrama, Mario
last_name: Valderrama
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Michel
full_name: Le Van Quyen, Michel
last_name: Le Van Quyen
citation:
ama: 'Valderrama M, Botella Soler V, Le Van Quyen M. Neuronal oscillations scale
up and scale down the brain dynamics . In: Meyer M, Pesenson Z, eds. Multiscale
Analysis and Nonlinear Dynamics: From Genes to the Brain. Wiley-VCH; 2013.
doi:10.1002/9783527671632.ch08'
apa: 'Valderrama, M., Botella Soler, V., & Le Van Quyen, M. (2013). Neuronal
oscillations scale up and scale down the brain dynamics . In M. Meyer & Z.
Pesenson (Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to
the Brain. Wiley-VCH. https://doi.org/10.1002/9783527671632.ch08'
chicago: 'Valderrama, Mario, Vicente Botella Soler, and Michel Le Van Quyen. “Neuronal
Oscillations Scale up and Scale down the Brain Dynamics .” In Multiscale Analysis
and Nonlinear Dynamics: From Genes to the Brain, edited by Misha Meyer and
Z. Pesenson. Wiley-VCH, 2013. https://doi.org/10.1002/9783527671632.ch08.'
ieee: 'M. Valderrama, V. Botella Soler, and M. Le Van Quyen, “Neuronal oscillations
scale up and scale down the brain dynamics ,” in Multiscale Analysis and Nonlinear
Dynamics: From Genes to the Brain, M. Meyer and Z. Pesenson, Eds. Wiley-VCH,
2013.'
ista: 'Valderrama M, Botella Soler V, Le Van Quyen M. 2013.Neuronal oscillations
scale up and scale down the brain dynamics . In: Multiscale Analysis and Nonlinear
Dynamics: From Genes to the Brain. Reviews of Nonlinear Dynamics and Complexity,
.'
mla: 'Valderrama, Mario, et al. “Neuronal Oscillations Scale up and Scale down the
Brain Dynamics .” Multiscale Analysis and Nonlinear Dynamics: From Genes to
the Brain, edited by Misha Meyer and Z. Pesenson, Wiley-VCH, 2013, doi:10.1002/9783527671632.ch08.'
short: 'M. Valderrama, V. Botella Soler, M. Le Van Quyen, in:, M. Meyer, Z. Pesenson
(Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, Wiley-VCH,
2013.'
date_created: 2018-12-11T11:57:31Z
date_published: 2013-08-01T00:00:00Z
date_updated: 2021-01-12T06:57:20Z
day: '01'
department:
- _id: GaTk
doi: 10.1002/9783527671632.ch08
editor:
- first_name: Misha
full_name: Meyer, Misha
last_name: Meyer
- first_name: Z.
full_name: Pesenson, Z.
last_name: Pesenson
language:
- iso: eng
month: '08'
oa_version: None
publication: 'Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain'
publication_identifier:
eisbn:
- '9783527671632'
isbn:
- '9783527411986 '
publication_status: published
publisher: Wiley-VCH
publist_id: '4513'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Neuronal oscillations scale up and scale down the brain dynamics '
type: book_chapter
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2013'
...
---
_id: '2818'
abstract:
- lang: eng
text: Models of neural responses to stimuli with complex spatiotemporal correlation
structure often assume that neurons are selective for only a small number of linear
projections of a potentially high-dimensional input. In this review, we explore
recent modeling approaches where the neural response depends on the quadratic
form of the input rather than on its linear projection, that is, the neuron is
sensitive to the local covariance structure of the signal preceding the spike.
To infer this quadratic dependence in the presence of arbitrary (e.g., naturalistic)
stimulus distribution, we review several inference methods, focusing in particular
on two information theory–based approaches (maximization of stimulus energy and
of noise entropy) and two likelihood-based approaches (Bayesian spike-triggered
covariance and extensions of generalized linear models). We analyze the formal
relationship between the likelihood-based and information-based approaches to
demonstrate how they lead to consistent inference. We demonstrate the practical
feasibility of these procedures by using model neurons responding to a flickering
variance stimulus.
author:
- first_name: Kanaka
full_name: Rajan, Kanaka
last_name: Rajan
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Rajan K, Marre O, Tkačik G. Learning quadratic receptive fields from neural
responses to natural stimuli. Neural Computation. 2013;25(7):1661-1692.
doi:10.1162/NECO_a_00463
apa: Rajan, K., Marre, O., & Tkačik, G. (2013). Learning quadratic receptive
fields from neural responses to natural stimuli. Neural Computation. MIT
Press . https://doi.org/10.1162/NECO_a_00463
chicago: Rajan, Kanaka, Olivier Marre, and Gašper Tkačik. “Learning Quadratic Receptive
Fields from Neural Responses to Natural Stimuli.” Neural Computation. MIT
Press , 2013. https://doi.org/10.1162/NECO_a_00463.
ieee: K. Rajan, O. Marre, and G. Tkačik, “Learning quadratic receptive fields from
neural responses to natural stimuli,” Neural Computation, vol. 25, no.
7. MIT Press , pp. 1661–1692, 2013.
ista: Rajan K, Marre O, Tkačik G. 2013. Learning quadratic receptive fields from
neural responses to natural stimuli. Neural Computation. 25(7), 1661–1692.
mla: Rajan, Kanaka, et al. “Learning Quadratic Receptive Fields from Neural Responses
to Natural Stimuli.” Neural Computation, vol. 25, no. 7, MIT Press , 2013,
pp. 1661–92, doi:10.1162/NECO_a_00463.
short: K. Rajan, O. Marre, G. Tkačik, Neural Computation 25 (2013) 1661–1692.
date_created: 2018-12-11T11:59:45Z
date_published: 2013-07-01T00:00:00Z
date_updated: 2021-01-12T06:59:56Z
day: '01'
department:
- _id: GaTk
doi: 10.1162/NECO_a_00463
external_id:
arxiv:
- '1209.0121'
intvolume: ' 25'
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1209.0121
month: '07'
oa: 1
oa_version: Preprint
page: 1661 - 1692
publication: Neural Computation
publication_status: published
publisher: 'MIT Press '
publist_id: '3983'
quality_controlled: '1'
scopus_import: 1
status: public
title: Learning quadratic receptive fields from neural responses to natural stimuli
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 25
year: '2013'
...
---
_id: '2850'
abstract:
- lang: eng
text: "Recent work emphasizes that the maximum entropy principle provides a bridge
between statistical mechanics models for collective behavior in neural networks
and experiments on networks of real neurons. Most of this work has focused on
capturing the measured correlations among pairs of neurons. Here we suggest an
alternative, constructing models that are consistent with the distribution of
global network activity, i.e. the probability that K out of N cells in the network
generate action potentials in the same small time bin. The inverse problem that
we need to solve in constructing the model is analytically tractable, and provides
a natural 'thermodynamics' for the network in the limit of large N. We analyze
the responses of neurons in a small patch of the retina to naturalistic stimuli,
and find that the implied thermodynamics is very close to an unusual critical
point, in which the entropy (in proper units) is exactly equal to the energy.
© 2013 IOP Publishing Ltd and SISSA Medialab srl.\r\n"
acknowledgement: "his work was supported in part by NSF Grants IIS-0613435 and PHY-0957573,
by NIH Grants R01 EY14196 and P50 GM071508, by the Fannie and John Hertz Foundation,
by the Human Frontiers Science Program, by the Swartz Foundation, and by the WM
Keck Foundation.\r\n"
article_number: P03011
article_processing_charge: No
article_type: original
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Dario
full_name: Amodei, Dario
last_name: Amodei
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. The simplest maximum
entropy model for collective behavior in a neural network. Journal of Statistical
Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03011
apa: Tkačik, G., Marre, O., Mora, T., Amodei, D., Berry, M., & Bialek, W. (2013).
The simplest maximum entropy model for collective behavior in a neural network.
Journal of Statistical Mechanics Theory and Experiment. IOP Publishing
Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03011
chicago: Tkačik, Gašper, Olivier Marre, Thierry Mora, Dario Amodei, Michael Berry,
and William Bialek. “The Simplest Maximum Entropy Model for Collective Behavior
in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment.
IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03011.
ieee: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, and W. Bialek, “The simplest
maximum entropy model for collective behavior in a neural network,” Journal
of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing
Ltd., 2013.
ista: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. 2013. The simplest
maximum entropy model for collective behavior in a neural network. Journal of
Statistical Mechanics Theory and Experiment. 2013(3), P03011.
mla: Tkačik, Gašper, et al. “The Simplest Maximum Entropy Model for Collective Behavior
in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment,
vol. 2013, no. 3, P03011, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03011.
short: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, W. Bialek, Journal of
Statistical Mechanics Theory and Experiment 2013 (2013).
date_created: 2018-12-11T11:59:55Z
date_published: 2013-03-12T00:00:00Z
date_updated: 2021-01-12T07:00:14Z
day: '12'
department:
- _id: GaTk
doi: 10.1088/1742-5468/2013/03/P03011
external_id:
arxiv:
- '1207.6319'
intvolume: ' 2013'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1207.6319
month: '03'
oa: 1
oa_version: Preprint
publication: Journal of Statistical Mechanics Theory and Experiment
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '3942'
quality_controlled: '1'
scopus_import: 1
status: public
title: The simplest maximum entropy model for collective behavior in a neural network
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2013
year: '2013'
...
---
_id: '2851'
abstract:
- lang: eng
text: The number of possible activity patterns in a population of neurons grows
exponentially with the size of the population. Typical experiments explore only
a tiny fraction of the large space of possible activity patterns in the case of
populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled
regime, to estimate the probabilities with which most of the activity patterns
occur. As a result, the corresponding entropy - which is a measure of the computational
power of the neural population - cannot be estimated directly. We propose a simple
scheme for estimating the entropy in the undersampled regime, which bounds its
value from both below and above. The lower bound is the usual 'naive' entropy
of the experimental frequencies. The upper bound results from a hybrid approximation
of the entropy which makes use of the naive estimate, a maximum entropy fit, and
a coverage adjustment. We apply our simple scheme to artificial data, in order
to check their accuracy; we also compare its performance to those of several previously
defined entropy estimators. We then apply it to actual measurements of neural
activity in populations with up to 100 cells. Finally, we discuss the similarities
and differences between the proposed simple estimation scheme and various earlier
methods. © 2013 IOP Publishing Ltd and SISSA Medialab srl.
article_number: P03015
author:
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Julien
full_name: Dubuis, Julien
last_name: Dubuis
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Ravá
full_name: Da Silveira, Ravá
last_name: Da Silveira
citation:
ama: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. A simple method for estimating
the entropy of neural activity. Journal of Statistical Mechanics Theory and
Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03015
apa: Berry, M., Tkačik, G., Dubuis, J., Marre, O., & Da Silveira, R. (2013).
A simple method for estimating the entropy of neural activity. Journal of Statistical
Mechanics Theory and Experiment. IOP Publishing Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03015
chicago: Berry, Michael, Gašper Tkačik, Julien Dubuis, Olivier Marre, and Ravá Da
Silveira. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal
of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd., 2013.
https://doi.org/10.1088/1742-5468/2013/03/P03015.
ieee: M. Berry, G. Tkačik, J. Dubuis, O. Marre, and R. Da Silveira, “A simple method
for estimating the entropy of neural activity,” Journal of Statistical Mechanics
Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013.
ista: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. 2013. A simple method
for estimating the entropy of neural activity. Journal of Statistical Mechanics
Theory and Experiment. 2013(3), P03015.
mla: Berry, Michael, et al. “A Simple Method for Estimating the Entropy of Neural
Activity.” Journal of Statistical Mechanics Theory and Experiment, vol.
2013, no. 3, P03015, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03015.
short: M. Berry, G. Tkačik, J. Dubuis, O. Marre, R. Da Silveira, Journal of Statistical
Mechanics Theory and Experiment 2013 (2013).
date_created: 2018-12-11T11:59:56Z
date_published: 2013-03-12T00:00:00Z
date_updated: 2021-01-12T07:00:14Z
day: '12'
department:
- _id: GaTk
doi: 10.1088/1742-5468/2013/03/P03015
intvolume: ' 2013'
issue: '3'
language:
- iso: eng
month: '03'
oa_version: None
publication: Journal of Statistical Mechanics Theory and Experiment
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '3941'
quality_controlled: '1'
scopus_import: 1
status: public
title: A simple method for estimating the entropy of neural activity
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2013
year: '2013'
...
---
_id: '2863'
abstract:
- lang: eng
text: Neural populations encode information about their stimulus in a collective
fashion, by joint activity patterns of spiking and silence. A full account of
this mapping from stimulus to neural activity is given by the conditional probability
distribution over neural codewords given the sensory input. For large populations,
direct sampling of these distributions is impossible, and so we must rely on constructing
appropriate models. We show here that in a population of 100 retinal ganglion
cells in the salamander retina responding to temporal white-noise stimuli, dependencies
between cells play an important encoding role. We introduce the stimulus-dependent
maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear
model of a single neuron, to a pairwise-coupled neural population. We find that
the SDME model gives a more accurate account of single cell responses and in particular
significantly outperforms uncoupled models in reproducing the distributions of
population codewords emitted in response to a stimulus. We show how the SDME model,
in conjunction with static maximum entropy models of population vocabulary, can
be used to estimate information-theoretic quantities like average surprise and
information transmission in a neural population.
article_number: e1002922
author:
- first_name: Einat
full_name: Granot Atedgi, Einat
last_name: Granot Atedgi
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Ronen
full_name: Segev, Ronen
last_name: Segev
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. Stimulus-dependent maximum
entropy models of neural population codes. PLoS Computational Biology.
2013;9(3). doi:10.1371/journal.pcbi.1002922
apa: Granot Atedgi, E., Tkačik, G., Segev, R., & Schneidman, E. (2013). Stimulus-dependent
maximum entropy models of neural population codes. PLoS Computational Biology.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1002922
chicago: Granot Atedgi, Einat, Gašper Tkačik, Ronen Segev, and Elad Schneidman.
“Stimulus-Dependent Maximum Entropy Models of Neural Population Codes.” PLoS
Computational Biology. Public Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1002922.
ieee: E. Granot Atedgi, G. Tkačik, R. Segev, and E. Schneidman, “Stimulus-dependent
maximum entropy models of neural population codes,” PLoS Computational Biology,
vol. 9, no. 3. Public Library of Science, 2013.
ista: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. 2013. Stimulus-dependent
maximum entropy models of neural population codes. PLoS Computational Biology.
9(3), e1002922.
mla: Granot Atedgi, Einat, et al. “Stimulus-Dependent Maximum Entropy Models of
Neural Population Codes.” PLoS Computational Biology, vol. 9, no. 3, e1002922,
Public Library of Science, 2013, doi:10.1371/journal.pcbi.1002922.
short: E. Granot Atedgi, G. Tkačik, R. Segev, E. Schneidman, PLoS Computational
Biology 9 (2013).
date_created: 2018-12-11T12:00:00Z
date_published: 2013-03-01T00:00:00Z
date_updated: 2021-01-12T07:00:20Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1002922
file:
- access_level: open_access
checksum: 5a30876c193209fa05b26db71845dd16
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:45Z
date_updated: 2020-07-14T12:45:52Z
file_id: '5099'
file_name: IST-2013-120-v1+1_journal.pcbi.1002922.pdf
file_size: 1548120
relation: main_file
file_date_updated: 2020-07-14T12:45:52Z
has_accepted_license: '1'
intvolume: ' 9'
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '3926'
pubrep_id: '120'
quality_controlled: '1'
scopus_import: 1
status: public
title: Stimulus-dependent maximum entropy models of neural population codes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2013'
...
---
_id: '2861'
abstract:
- lang: eng
text: We consider a two-parameter family of piecewise linear maps in which the moduli
of the two slopes take different values. We provide numerical evidence of the
existence of some parameter regions in which the Lyapunov exponent and the topological
entropy remain constant. Analytical proof of this phenomenon is also given for
certain cases. Surprisingly however, the systems with that property are not conjugate
as we prove by using kneading theory.
article_number: '125101'
author:
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: José
full_name: Oteo, José
last_name: Oteo
- first_name: Javier
full_name: Ros, Javier
last_name: Ros
- first_name: Paul
full_name: Glendinning, Paul
last_name: Glendinning
citation:
ama: 'Botella Soler V, Oteo J, Ros J, Glendinning P. Lyapunov exponent and topological
entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical
and Theoretical. 2013;46(12). doi:10.1088/1751-8113/46/12/125101'
apa: 'Botella Soler, V., Oteo, J., Ros, J., & Glendinning, P. (2013). Lyapunov
exponent and topological entropy plateaus in piecewise linear maps. Journal
of Physics A: Mathematical and Theoretical. IOP Publishing Ltd. https://doi.org/10.1088/1751-8113/46/12/125101'
chicago: 'Botella Soler, Vicente, José Oteo, Javier Ros, and Paul Glendinning. “Lyapunov
Exponent and Topological Entropy Plateaus in Piecewise Linear Maps.” Journal
of Physics A: Mathematical and Theoretical. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1751-8113/46/12/125101.'
ieee: 'V. Botella Soler, J. Oteo, J. Ros, and P. Glendinning, “Lyapunov exponent
and topological entropy plateaus in piecewise linear maps,” Journal of Physics
A: Mathematical and Theoretical, vol. 46, no. 12. IOP Publishing Ltd., 2013.'
ista: 'Botella Soler V, Oteo J, Ros J, Glendinning P. 2013. Lyapunov exponent and
topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical
and Theoretical. 46(12), 125101.'
mla: 'Botella Soler, Vicente, et al. “Lyapunov Exponent and Topological Entropy
Plateaus in Piecewise Linear Maps.” Journal of Physics A: Mathematical and
Theoretical, vol. 46, no. 12, 125101, IOP Publishing Ltd., 2013, doi:10.1088/1751-8113/46/12/125101.'
short: 'V. Botella Soler, J. Oteo, J. Ros, P. Glendinning, Journal of Physics A:
Mathematical and Theoretical 46 (2013).'
date_created: 2018-12-11T11:59:59Z
date_published: 2013-03-29T00:00:00Z
date_updated: 2021-01-12T07:00:19Z
day: '29'
department:
- _id: GaTk
doi: 10.1088/1751-8113/46/12/125101
intvolume: ' 46'
issue: '12'
language:
- iso: eng
month: '03'
oa_version: None
publication: 'Journal of Physics A: Mathematical and Theoretical'
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '3928'
quality_controlled: '1'
scopus_import: 1
status: public
title: Lyapunov exponent and topological entropy plateaus in piecewise linear maps
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 46
year: '2013'
...
---
_id: '2913'
abstract:
- lang: eng
text: 'The ability of an organism to distinguish between various stimuli is limited
by the structure and noise in the population code of its sensory neurons. Here
we infer a distance measure on the stimulus space directly from the recorded activity
of 100 neurons in the salamander retina. In contrast to previously used measures
of stimulus similarity, this "neural metric" tells us how distinguishable
a pair of stimulus clips is to the retina, based on the similarity between the
induced distributions of population responses. We show that the retinal distance
strongly deviates from Euclidean, or any static metric, yet has a simple structure:
we identify the stimulus features that the neural population is jointly sensitive
to, and show the support-vector-machine- like kernel function relating the stimulus
and neural response spaces. We show that the non-Euclidean nature of the retinal
distance has important consequences for neural decoding.'
article_number: '058104'
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Einat
full_name: Granot Atedgi, Einat
last_name: Granot Atedgi
- first_name: Ronen
full_name: Segev, Ronen
last_name: Segev
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. Retinal metric: a stimulus
distance measure derived from population neural responses. Physical Review
Letters. 2013;110(5). doi:10.1103/PhysRevLett.110.058104'
apa: 'Tkačik, G., Granot Atedgi, E., Segev, R., & Schneidman, E. (2013). Retinal
metric: a stimulus distance measure derived from population neural responses.
Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.110.058104'
chicago: 'Tkačik, Gašper, Einat Granot Atedgi, Ronen Segev, and Elad Schneidman.
“Retinal Metric: A Stimulus Distance Measure Derived from Population Neural Responses.”
Physical Review Letters. American Physical Society, 2013. https://doi.org/10.1103/PhysRevLett.110.058104.'
ieee: 'G. Tkačik, E. Granot Atedgi, R. Segev, and E. Schneidman, “Retinal metric:
a stimulus distance measure derived from population neural responses,” Physical
Review Letters, vol. 110, no. 5. American Physical Society, 2013.'
ista: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. 2013. Retinal metric: a
stimulus distance measure derived from population neural responses. Physical Review
Letters. 110(5), 058104.'
mla: 'Tkačik, Gašper, et al. “Retinal Metric: A Stimulus Distance Measure Derived
from Population Neural Responses.” Physical Review Letters, vol. 110, no.
5, 058104, American Physical Society, 2013, doi:10.1103/PhysRevLett.110.058104.'
short: G. Tkačik, E. Granot Atedgi, R. Segev, E. Schneidman, Physical Review Letters
110 (2013).
date_created: 2018-12-11T12:00:18Z
date_published: 2013-01-28T00:00:00Z
date_updated: 2021-01-12T07:00:39Z
day: '28'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.110.058104
intvolume: ' 110'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1205.6598
month: '01'
oa: 1
oa_version: Preprint
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '3830'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Retinal metric: a stimulus distance measure derived from population neural
responses'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 110
year: '2013'
...
---
_id: '3261'
abstract:
- lang: eng
text: Cells in a developing embryo have no direct way of "measuring" their
physical position. Through a variety of processes, however, the expression levels
of multiple genes come to be correlated with position, and these expression levels
thus form a code for "positional information." We show how to measure
this information, in bits, using the gap genes in the Drosophila embryo as an
example. Individual genes carry nearly two bits of information, twice as much
as expected if the expression patterns consisted only of on/off domains separated
by sharp boundaries. Taken together, four gap genes carry enough information to
define a cell's location with an error bar of ~1% along the anterior-posterior
axis of the embryo. This precision is nearly enough for each cell to have a unique
identity, which is the maximum information the system can use, and is nearly constant
along the length of the embryo. We argue that this constancy is a signature of
optimality in the transmission of information from primary morphogen inputs to
the output of the gap gene network.
author:
- first_name: Julien
full_name: Dubuis, Julien
last_name: Dubuis
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Eric
full_name: Wieschaus, Eric
last_name: Wieschaus
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. Positional information,
in bits. PNAS. 2013;110(41):16301-16308. doi:10.1073/pnas.1315642110
apa: Dubuis, J., Tkačik, G., Wieschaus, E., Gregor, T., & Bialek, W. (2013).
Positional information, in bits. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1315642110
chicago: Dubuis, Julien, Gašper Tkačik, Eric Wieschaus, Thomas Gregor, and William
Bialek. “Positional Information, in Bits.” PNAS. National Academy of Sciences,
2013. https://doi.org/10.1073/pnas.1315642110.
ieee: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, and W. Bialek, “Positional
information, in bits,” PNAS, vol. 110, no. 41. National Academy of Sciences,
pp. 16301–16308, 2013.
ista: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. 2013. Positional information,
in bits. PNAS. 110(41), 16301–16308.
mla: Dubuis, Julien, et al. “Positional Information, in Bits.” PNAS, vol.
110, no. 41, National Academy of Sciences, 2013, pp. 16301–08, doi:10.1073/pnas.1315642110.
short: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, W. Bialek, PNAS 110 (2013)
16301–16308.
date_created: 2018-12-11T12:02:19Z
date_published: 2013-10-08T00:00:00Z
date_updated: 2021-01-12T07:42:13Z
day: '08'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1073/pnas.1315642110
external_id:
pmid:
- '24089448'
file:
- access_level: open_access
checksum: ecd859fe52a562193027d428b5524a8d
content_type: application/pdf
creator: dernst
date_created: 2019-01-22T13:53:23Z
date_updated: 2020-07-14T12:46:06Z
file_id: '5873'
file_name: 2013_PNAS_Dubuis.pdf
file_size: 1670548
relation: main_file
file_date_updated: 2020-07-14T12:46:06Z
has_accepted_license: '1'
intvolume: ' 110'
issue: '41'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 16301 - 16308
pmid: 1
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '3387'
quality_controlled: '1'
scopus_import: 1
status: public
title: Positional information, in bits
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 110
year: '2013'
...
---
_id: '499'
abstract:
- lang: eng
text: Exposure of an isogenic bacterial population to a cidal antibiotic typically
fails to eliminate a small fraction of refractory cells. Historically, fractional
killing has been attributed to infrequently dividing or nondividing "persisters."
Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium
smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although
persistence in these studies was characterized by stable numbers of cells, this
apparent stability was actually a dynamic state of balanced division and death.
Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic
pulses that were negatively correlated with cell survival. These behaviors may
reflect epigenetic effects, because KatG pulsing and death were correlated between
sibling cells. Selection of lineages characterized by infrequent KatG pulsing
could allow nonresponsive adaptation during prolonged drug exposure.
author:
- first_name: Yurichi
full_name: Wakamoto, Yurichi
last_name: Wakamoto
- first_name: Neraaj
full_name: Dhar, Neraaj
last_name: Dhar
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Katrin
full_name: Schneider, Katrin
last_name: Schneider
- first_name: François
full_name: Signorino Gelo, François
last_name: Signorino Gelo
- first_name: Stanislas
full_name: Leibler, Stanislas
last_name: Leibler
- first_name: John
full_name: Mckinney, John
last_name: Mckinney
citation:
ama: Wakamoto Y, Dhar N, Chait RP, et al. Dynamic persistence of antibiotic-stressed
mycobacteria. Science. 2013;339(6115):91-95. doi:10.1126/science.1229858
apa: Wakamoto, Y., Dhar, N., Chait, R. P., Schneider, K., Signorino Gelo, F., Leibler,
S., & Mckinney, J. (2013). Dynamic persistence of antibiotic-stressed mycobacteria.
Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.1229858
chicago: Wakamoto, Yurichi, Neraaj Dhar, Remy P Chait, Katrin Schneider, François
Signorino Gelo, Stanislas Leibler, and John Mckinney. “Dynamic Persistence of
Antibiotic-Stressed Mycobacteria.” Science. American Association for the
Advancement of Science, 2013. https://doi.org/10.1126/science.1229858.
ieee: Y. Wakamoto et al., “Dynamic persistence of antibiotic-stressed mycobacteria,”
Science, vol. 339, no. 6115. American Association for the Advancement of
Science, pp. 91–95, 2013.
ista: Wakamoto Y, Dhar N, Chait RP, Schneider K, Signorino Gelo F, Leibler S, Mckinney
J. 2013. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 339(6115),
91–95.
mla: Wakamoto, Yurichi, et al. “Dynamic Persistence of Antibiotic-Stressed Mycobacteria.”
Science, vol. 339, no. 6115, American Association for the Advancement of
Science, 2013, pp. 91–95, doi:10.1126/science.1229858.
short: Y. Wakamoto, N. Dhar, R.P. Chait, K. Schneider, F. Signorino Gelo, S. Leibler,
J. Mckinney, Science 339 (2013) 91–95.
date_created: 2018-12-11T11:46:48Z
date_published: 2013-01-04T00:00:00Z
date_updated: 2021-01-12T08:01:06Z
day: '04'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.1229858
intvolume: ' 339'
issue: '6115'
language:
- iso: eng
month: '01'
oa_version: None
page: 91 - 95
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7321'
quality_controlled: '1'
scopus_import: 1
status: public
title: Dynamic persistence of antibiotic-stressed mycobacteria
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 339
year: '2013'
...
---
_id: '2277'
abstract:
- lang: eng
text: Redundancies and correlations in the responses of sensory neurons may seem
to waste neural resources, but they can also carry cues about structured stimuli
and may help the brain to correct for response errors. To investigate the effect
of stimulus structure on redundancy in retina, we measured simultaneous responses
from populations of retinal ganglion cells presented with natural and artificial
stimuli that varied greatly in correlation structure; these stimuli and recordings
are publicly available online. Responding to spatio-temporally structured stimuli
such as natural movies, pairs of ganglion cells were modestly more correlated
than in response to white noise checkerboards, but they were much less correlated
than predicted by a non-adapting functional model of retinal response. Meanwhile,
responding to stimuli with purely spatial correlations, pairs of ganglion cells
showed increased correlations consistent with a static, non-adapting receptive
field and nonlinearity. We found that in response to spatio-temporally correlated
stimuli, ganglion cells had faster temporal kernels and tended to have stronger
surrounds. These properties of individual cells, along with gain changes that
opposed changes in effective contrast at the ganglion cell input, largely explained
the pattern of pairwise correlations across stimuli where receptive field measurements
were possible.
article_number: e1003344
author:
- first_name: Kristina
full_name: Simmons, Kristina
last_name: Simmons
- first_name: Jason
full_name: Prentice, Jason
last_name: Prentice
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Jan
full_name: Homann, Jan
last_name: Homann
- first_name: Heather
full_name: Yee, Heather
last_name: Yee
- first_name: Stephanie
full_name: Palmer, Stephanie
last_name: Palmer
- first_name: Philip
full_name: Nelson, Philip
last_name: Nelson
- first_name: Vijay
full_name: Balasubramanian, Vijay
last_name: Balasubramanian
citation:
ama: Simmons K, Prentice J, Tkačik G, et al. Transformation of stimulus correlations
by the retina. PLoS Computational Biology. 2013;9(12). doi:10.1371/journal.pcbi.1003344
apa: Simmons, K., Prentice, J., Tkačik, G., Homann, J., Yee, H., Palmer, S., … Balasubramanian,
V. (2013). Transformation of stimulus correlations by the retina. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1003344
chicago: Simmons, Kristina, Jason Prentice, Gašper Tkačik, Jan Homann, Heather Yee,
Stephanie Palmer, Philip Nelson, and Vijay Balasubramanian. “Transformation of
Stimulus Correlations by the Retina.” PLoS Computational Biology. Public
Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1003344.
ieee: K. Simmons et al., “Transformation of stimulus correlations by the
retina,” PLoS Computational Biology, vol. 9, no. 12. Public Library of
Science, 2013.
ista: Simmons K, Prentice J, Tkačik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian
V. 2013. Transformation of stimulus correlations by the retina. PLoS Computational
Biology. 9(12), e1003344.
mla: Simmons, Kristina, et al. “Transformation of Stimulus Correlations by the Retina.”
PLoS Computational Biology, vol. 9, no. 12, e1003344, Public Library of
Science, 2013, doi:10.1371/journal.pcbi.1003344.
short: K. Simmons, J. Prentice, G. Tkačik, J. Homann, H. Yee, S. Palmer, P. Nelson,
V. Balasubramanian, PLoS Computational Biology 9 (2013).
date_created: 2018-12-11T11:56:43Z
date_published: 2013-12-05T00:00:00Z
date_updated: 2023-02-23T14:07:04Z
day: '05'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1003344
file:
- access_level: open_access
checksum: 46722afc4f7eabb0831165d9c1b171ad
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:36Z
date_updated: 2020-07-14T12:45:36Z
file_id: '5089'
file_name: IST-2016-410-v1+1_journal.pcbi.1003344.pdf
file_size: 3115568
relation: main_file
file_date_updated: 2020-07-14T12:45:36Z
has_accepted_license: '1'
intvolume: ' 9'
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '4667'
pubrep_id: '410'
quality_controlled: '1'
related_material:
record:
- id: '9752'
relation: research_data
status: public
scopus_import: 1
status: public
title: Transformation of stimulus correlations by the retina
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2013'
...
---
_id: '2914'
abstract:
- lang: eng
text: The scale invariance of natural images suggests an analogy to the statistical
mechanics of physical systems at a critical point. Here we examine the distribution
of pixels in small image patches and show how to construct the corresponding thermodynamics.
We find evidence for criticality in a diverging specific heat, which corresponds
to large fluctuations in how "surprising" we find individual images,
and in the quantitative form of the entropy vs energy. We identify special image
configurations as local energy minima and show that average patches within each
basin are interpretable as lines and edges in all orientations.
acknowledgement: "This work was supported in part by NSF Grants No. IIS-0613435, No.
IBN-0344678, and No. PHY-0957573, by NIH Grant No. T32 MH065214, by the Human Frontier
Science Program, and by the Swartz Foundation.\r\nCC BY 3.0\r\n"
article_number: '018701'
article_processing_charge: No
article_type: original
author:
- first_name: Greg
full_name: Stephens, Greg
last_name: Stephens
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Stephens G, Mora T, Tkačik G, Bialek W. Statistical thermodynamics of natural
images. Physical Review Letters. 2013;110(1). doi:10.1103/PhysRevLett.110.018701
apa: Stephens, G., Mora, T., Tkačik, G., & Bialek, W. (2013). Statistical thermodynamics
of natural images. Physical Review Letters. American Physical Society.
https://doi.org/10.1103/PhysRevLett.110.018701
chicago: Stephens, Greg, Thierry Mora, Gašper Tkačik, and William Bialek. “Statistical
Thermodynamics of Natural Images.” Physical Review Letters. American Physical
Society, 2013. https://doi.org/10.1103/PhysRevLett.110.018701.
ieee: G. Stephens, T. Mora, G. Tkačik, and W. Bialek, “Statistical thermodynamics
of natural images,” Physical Review Letters, vol. 110, no. 1. American
Physical Society, 2013.
ista: Stephens G, Mora T, Tkačik G, Bialek W. 2013. Statistical thermodynamics of
natural images. Physical Review Letters. 110(1), 018701.
mla: Stephens, Greg, et al. “Statistical Thermodynamics of Natural Images.” Physical
Review Letters, vol. 110, no. 1, 018701, American Physical Society, 2013,
doi:10.1103/PhysRevLett.110.018701.
short: G. Stephens, T. Mora, G. Tkačik, W. Bialek, Physical Review Letters 110 (2013).
date_created: 2018-12-11T12:00:19Z
date_published: 2013-01-02T00:00:00Z
date_updated: 2023-09-04T11:47:51Z
day: '02'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.110.018701
external_id:
arxiv:
- '0806.2694'
file:
- access_level: open_access
checksum: 72bfbc2094c4680e8a8a6bed668cd06d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:44Z
date_updated: 2020-07-14T12:45:53Z
file_id: '5366'
file_name: IST-2016-401-v1+1_1281.full.pdf
file_size: 416965
relation: main_file
file_date_updated: 2020-07-14T12:45:53Z
has_accepted_license: '1'
intvolume: ' 110'
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '3829'
pubrep_id: '401'
quality_controlled: '1'
status: public
title: Statistical thermodynamics of natural images
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 110
year: '2013'
...