---
_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: '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: 2025-04-15T06:50:08Z
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: '9813'
abstract:
- lang: eng
text: 'File S1 contains figures that clarify the following features: (i) effect
of population size on the average number/frequency of SI classes, (ii) changes
in the minimal completeness deficit in time for a single class, and (iii) diversification
diagrams for all studied pathways, including the summary figure for k = 8. File
S2 contains the code required for a stochastic simulation of the SLF system with
an example. This file also includes the output in the form of figures and tables.'
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: Tadeas
full_name: Priklopil, Tadeas
id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
last_name: Priklopil
- first_name: David
full_name: Field, David
id: 419049E2-F248-11E8-B48F-1D18A9856A87
last_name: Field
orcid: 0000-0002-4014-8478
- 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: Melinda
full_name: Pickup, Melinda
id: 2C78037E-F248-11E8-B48F-1D18A9856A87
last_name: Pickup
orcid: 0000-0001-6118-0541
citation:
ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material
for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1
apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018).
Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1
chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society
of America, 2018. https://doi.org/10.25386/genetics.6148304.v1.
ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental
material for Bodova et al., 2018.” Genetics Society of America, 2018.
ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material
for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1.
mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018.
Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1.
short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).
date_created: 2021-08-06T13:04:32Z
date_published: 2018-04-30T00:00:00Z
date_updated: 2025-04-15T07:17:08Z
day: '30'
department:
- _id: NiBa
- _id: GaTk
doi: 10.25386/genetics.6148304.v1
main_file_link:
- open_access: '1'
url: https://doi.org/10.25386/genetics.6148304.v1
month: '04'
oa: 1
oa_version: Published Version
publisher: Genetics Society of America
related_material:
record:
- id: '316'
relation: used_in_publication
status: public
status: public
title: Supplemental material for Bodova et al., 2018
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2018'
...
---
_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. Proceedings of the National Academy of Sciences of the United
States of America. 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. Proceedings of the National Academy
of Sciences of the United States of America. 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.” Proceedings of the National Academy
of Sciences of the United States of America. 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,” Proceedings of the National Academy of Sciences
of the United States of America, 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. Proceedings of the National Academy of Sciences of the United
States of America. 115(1), 186–191.
mla: Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive,
and Sparse Coding.” Proceedings of the National Academy of Sciences of the
United States of America, 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, Proceedings of the National Academy of Sciences
of the United States of America 115 (2018) 186–191.
corr_author: '1'
date_created: 2018-12-11T11:47:04Z
date_published: 2018-01-02T00:00:00Z
date_updated: 2025-05-14T10:55:59Z
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: Proceedings of the National Academy of Sciences of the United States
of America
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 115
year: '2018'
...
---
_id: '5584'
abstract:
- lang: eng
text: "This package contains data for the publication \"Nonlinear decoding of a
complex movie from the mammalian retina\" by Deny S. et al, PLOS Comput Biol (2018).
\r\n\r\nThe data consists of\r\n(i) 91 spike sorted, isolated rat retinal ganglion
cells that pass stability and quality criteria, recorded on the multi-electrode
array, in response to the presentation of the complex movie with many randomly
moving dark discs. The responses are represented as 648000 x 91 binary matrix,
where the first index indicates the timebin of duration 12.5 ms, and the second
index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike
in the particular time bin.\r\n(ii) README file and a graphical illustration of
the structure of the experiment, specifying how the 648000 timebins are split
into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments
are exact repeats or unique ball trajectories.\r\n(iii) a 648000 x 400 matrix
of luminance traces for each of the 20 x 20 positions (\"sites\") in the movie
frame, with time that is locked to the recorded raster. The luminance traces are
produced as described in the manuscript by filtering the raw disc movie with a
small gaussian spatial kernel. "
article_processing_charge: No
author:
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Vicente
full_name: Botella-Soler, Vicente
last_name: Botella-Soler
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding
of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98
apa: Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018).
Nonlinear decoding of a complex movie from the mammalian retina. Institute of
Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98
chicago: Deny, Stephane, Olivier Marre, Vicente Botella-Soler, Georg S Martius,
and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.”
Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:98.
ieee: S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkačik, “Nonlinear
decoding of a complex movie from the mammalian retina.” Institute of Science and
Technology Austria, 2018.
ista: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding
of a complex movie from the mammalian retina, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:98.
mla: Deny, Stephane, et al. Nonlinear Decoding of a Complex Movie from the Mammalian
Retina. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:98.
short: S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018).
datarep_id: '98'
date_created: 2018-12-12T12:31:39Z
date_published: 2018-03-29T00:00:00Z
date_updated: 2025-04-15T08:18:24Z
day: '29'
ddc:
- '570'
department:
- _id: ChLa
- _id: GaTk
doi: 10.15479/AT:ISTA:98
file:
- access_level: open_access
checksum: 6808748837b9afbbbabc2a356ca2b88a
content_type: application/octet-stream
creator: system
date_created: 2018-12-12T13:02:24Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5590'
file_name: IST-2018-98-v1+1_BBalls_area2_tile2_20x20.mat
file_size: 1142543971
relation: main_file
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checksum: d6d6cd07743038fe3a12352983fcf9dd
content_type: application/pdf
creator: system
date_created: 2018-12-12T13:02:25Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5591'
file_name: IST-2018-98-v1+2_ExperimentStructure.pdf
file_size: 702336
relation: main_file
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checksum: 0c9cfb4dab35bb3dc25a04395600b1c8
content_type: application/octet-stream
creator: system
date_created: 2018-12-12T13:02:26Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5592'
file_name: IST-2018-98-v1+3_GoodLocations_area2_20x20.mat
file_size: 432
relation: main_file
- access_level: open_access
checksum: 2a83b011012e21e934b4596285b1a183
content_type: text/plain
creator: system
date_created: 2018-12-12T13:02:26Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5593'
file_name: IST-2018-98-v1+4_README.txt
file_size: 986
relation: main_file
file_date_updated: 2020-07-14T12:47:07Z
has_accepted_license: '1'
keyword:
- retina
- decoding
- regression
- neural networks
- complex stimulus
month: '03'
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
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '292'
relation: used_in_publication
status: public
status: public
title: Nonlinear decoding of a complex movie from the mammalian retina
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '5587'
abstract:
- lang: eng
text: "Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E.
coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix
enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose
limited minimal medium, \r\nobtained from the soichiometric matrix by standard
linear algebra (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John
ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in
a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter
of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli
catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with
the Lovasz method.\r\n\r\nlovasz.cpp \r\nThis c++ code file receives in input
the polytope of the feasible steady states of a metabolic network, \r\n(matrix
and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding
the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults
to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we
refer to PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp \r\nThis c++
code file receives in input the polytope of the feasible steady states of a metabolic
network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point
inside and \r\nit gives in output a max entropy sampling at fixed average growth
rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov
chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli
network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015)."
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: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62
apa: De Martino, D., & Tkačik, G. (2018). Supporting materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:62
chicago: De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science
and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62.
ieee: D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology
Austria, 2018.
ista: De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:62.
mla: De Martino, Daniele, and Gašper Tkačik. Supporting Materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria, 2018, doi:10.15479/AT:ISTA:62.
short: D. De Martino, G. Tkačik, (2018).
datarep_id: '111'
date_created: 2018-12-12T12:31:41Z
date_published: 2018-09-21T00:00:00Z
date_updated: 2025-04-15T06:50:08Z
day: '21'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:62
ec_funded: 1
file:
- access_level: open_access
checksum: 97992e3e8cf8544ec985a48971708726
content_type: application/zip
creator: system
date_created: 2018-12-12T13:05:13Z
date_updated: 2020-07-14T12:47:08Z
file_id: '5641'
file_name: IST-2018-111-v1+1_CODES.zip
file_size: 14376
relation: main_file
file_date_updated: 2020-07-14T12:47:08Z
has_accepted_license: '1'
keyword:
- metabolic networks
- e.coli core
- maximum entropy
- monte carlo markov chain sampling
- ellipsoidal rounding
month: '09'
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
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '161'
relation: research_paper
status: public
status: public
title: Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE
GROWTH"
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
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
arxiv: 1
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.'
corr_author: '1'
date_created: 2018-12-11T11:47:28Z
date_published: 2018-08-01T00:00:00Z
date_updated: 2024-10-09T20:58:45Z
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: '9831'
abstract:
- lang: eng
text: 'Implementation of the inference method in Matlab, including three applications
of the method: The first one for the model of ant motion, the second one for bacterial
chemotaxis, and the third one for the motion of fish.'
article_processing_charge: No
author:
- first_name: Katarína
full_name: Bod’Ová, Katarína
last_name: Bod’Ová
- first_name: Gabriel
full_name: Mitchell, Gabriel
id: 315BCD80-F248-11E8-B48F-1D18A9856A87
last_name: Mitchell
- first_name: Roy
full_name: Harpaz, Roy
last_name: Harpaz
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Implementation of
the inference method in Matlab. 2018. doi:10.1371/journal.pone.0193049.s001
apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018).
Implementation of the inference method in Matlab. Public Library of Science. https://doi.org/10.1371/journal.pone.0193049.s001
chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper
Tkačik. “Implementation of the Inference Method in Matlab.” Public Library of
Science, 2018. https://doi.org/10.1371/journal.pone.0193049.s001.
ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Implementation
of the inference method in Matlab.” Public Library of Science, 2018.
ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Implementation
of the inference method in Matlab, Public Library of Science, 10.1371/journal.pone.0193049.s001.
mla: Bod’Ová, Katarína, et al. Implementation of the Inference Method in Matlab.
Public Library of Science, 2018, doi:10.1371/journal.pone.0193049.s001.
short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, (2018).
date_created: 2021-08-09T07:01:24Z
date_published: 2018-03-07T00:00:00Z
date_updated: 2025-04-15T06:44:30Z
day: '07'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0193049.s001
month: '03'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '406'
relation: used_in_publication
status: public
status: public
title: Implementation of the inference method in Matlab
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2018'
...
---
_id: '406'
abstract:
- lang: eng
text: 'Recent developments in automated tracking allow uninterrupted, high-resolution
recording of animal trajectories, sometimes coupled with the identification of
stereotyped changes of body pose or other behaviors of interest. Analysis and
interpretation of such data represents a challenge: the timing of animal behaviors
may be stochastic and modulated by kinematic variables, by the interaction with
the environment or with the conspecifics within the animal group, and dependent
on internal cognitive or behavioral state of the individual. Existing models for
collective motion typically fail to incorporate the discrete, stochastic, and
internal-state-dependent aspects of behavior, while models focusing on individual
animal behavior typically ignore the spatial aspects of the problem. Here we propose
a probabilistic modeling framework to address this gap. Each animal can switch
stochastically between different behavioral states, with each state resulting
in a possibly different law of motion through space. Switching rates for behavioral
transitions can depend in a very general way, which we seek to identify from data,
on the effects of the environment as well as the interaction between the animals.
We represent the switching dynamics as a Generalized Linear Model and show that:
(i) forward simulation of multiple interacting animals is possible using a variant
of the Gillespie’s Stochastic Simulation Algorithm; (ii) formulated properly,
the maximum likelihood inference of switching rate functions is tractably solvable
by gradient descent; (iii) model selection can be used to identify factors that
modulate behavioral state switching and to appropriately adjust model complexity
to data. To illustrate our framework, we apply it to two synthetic models of animal
motion and to real zebrafish tracking data. '
acknowledgement: This work was supported by the Human Frontier Science Program RGP0065/2012
(GT, ES).
article_processing_charge: Yes
author:
- first_name: Katarína
full_name: Bod’Ová, Katarína
last_name: Bod’Ová
- first_name: Gabriel
full_name: Mitchell, Gabriel
id: 315BCD80-F248-11E8-B48F-1D18A9856A87
last_name: Mitchell
- first_name: Roy
full_name: Harpaz, Roy
last_name: Harpaz
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Probabilistic models
of individual and collective animal behavior. PLoS One. 2018;13(3). doi:10.1371/journal.pone.0193049
apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018).
Probabilistic models of individual and collective animal behavior. PLoS One.
Public Library of Science. https://doi.org/10.1371/journal.pone.0193049
chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper
Tkačik. “Probabilistic Models of Individual and Collective Animal Behavior.” PLoS
One. Public Library of Science, 2018. https://doi.org/10.1371/journal.pone.0193049.
ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Probabilistic
models of individual and collective animal behavior,” PLoS One, vol. 13,
no. 3. Public Library of Science, 2018.
ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Probabilistic
models of individual and collective animal behavior. PLoS One. 13(3).
mla: Bod’Ová, Katarína, et al. “Probabilistic Models of Individual and Collective
Animal Behavior.” PLoS One, vol. 13, no. 3, Public Library of Science,
2018, doi:10.1371/journal.pone.0193049.
short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, PLoS One 13
(2018).
corr_author: '1'
date_created: 2018-12-11T11:46:18Z
date_published: 2018-03-07T00:00:00Z
date_updated: 2025-04-15T06:44:30Z
day: '07'
ddc:
- '530'
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0193049
external_id:
isi:
- '000426896800032'
file:
- access_level: open_access
checksum: 684229493db75b43e98a46cd922da497
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:15:43Z
date_updated: 2020-07-14T12:46:22Z
file_id: '5165'
file_name: IST-2018-995-v1+1_2018_Bodova_Probabilistic.pdf
file_size: 6887358
relation: main_file
file_date_updated: 2020-07-14T12:46:22Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Submitted Version
project:
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '7423'
pubrep_id: '995'
quality_controlled: '1'
related_material:
record:
- id: '9831'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Probabilistic models of individual and collective animal behavior
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: 13
year: '2018'
...
---
_id: '281'
abstract:
- lang: eng
text: 'Although cells respond specifically to environments, how environmental identity
is encoded intracellularly is not understood. Here, we study this organization
of information in budding yeast by estimating the mutual information between environmental
transitions and the dynamics of nuclear translocation for 10 transcription factors.
Our method of estimation is general, scalable, and based on decoding from single
cells. The dynamics of the transcription factors are necessary to encode the highest
amounts of extracellular information, and we show that information is transduced
through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can
encode the nature of multiple stresses, but only if stress is high; specialists
(Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly
and for a wider range of magnitudes. In particular, Dot6 encodes almost as much
information as Msn2, the master regulator of the environmental stress response.
Each transcription factor reports differently, and it is only their collective
behavior that distinguishes between multiple environmental states. Changes in
the dynamics of the localization of transcription factors thus constitute a precise,
distributed internal representation of extracellular change. We predict that such
multidimensional representations are common in cellular decision-making.'
acknowledgement: This work was supported by the Biotechnology and Biological Sciences
Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences
Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to
G.T.).
article_processing_charge: No
article_type: original
author:
- first_name: Alejandro
full_name: Granados, Alejandro
last_name: Granados
- first_name: Julian
full_name: Pietsch, Julian
last_name: Pietsch
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Isebail
full_name: Farquhar, Isebail
last_name: Farquhar
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Peter
full_name: Swain, Peter
last_name: Swain
citation:
ama: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed
and dynamic intracellular organization of extracellular information. PNAS.
2018;115(23):6088-6093. doi:10.1073/pnas.1716659115
apa: Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G.,
& Swain, P. (2018). Distributed and dynamic intracellular organization of
extracellular information. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1716659115
chicago: Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar,
Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS. National Academy of Sciences, 2018.
https://doi.org/10.1073/pnas.1716659115.
ieee: A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and
P. Swain, “Distributed and dynamic intracellular organization of extracellular
information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp.
6088–6093, 2018.
ista: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018.
Distributed and dynamic intracellular organization of extracellular information.
PNAS. 115(23), 6088–6093.
mla: Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS, vol. 115, no. 23, National Academy
of Sciences, 2018, pp. 6088–93, doi:10.1073/pnas.1716659115.
short: A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P.
Swain, PNAS 115 (2018) 6088–6093.
date_created: 2018-12-11T11:45:35Z
date_published: 2018-06-05T00:00:00Z
date_updated: 2026-04-08T13:55:45Z
day: '05'
department:
- _id: GaTk
doi: 10.1073/pnas.1716659115
external_id:
isi:
- '000434114900071'
pmid:
- '29784812'
intvolume: ' 115'
isi: 1
issue: '23'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/early/2017/09/21/192039
month: '06'
oa: 1
oa_version: Preprint
page: 6088 - 6093
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7618'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Distributed and dynamic intracellular organization of extracellular information
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '457'
abstract:
- lang: eng
text: Temperate bacteriophages integrate in bacterial genomes as prophages and represent
an important source of genetic variation for bacterial evolution, frequently transmitting
fitness-augmenting genes such as toxins responsible for virulence of major pathogens.
However, only a fraction of bacteriophage infections are lysogenic and lead to
prophage acquisition, whereas the majority are lytic and kill the infected bacteria.
Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity
to bacteriophages are expected to act as a double-edged sword and increase the
odds of survival at the cost of depriving bacteria of potentially beneficial prophages.
We show that although restriction-modification systems as mechanisms of innate
immunity prevent both lytic and lysogenic infections indiscriminately in individual
bacteria, they increase the number of prophage-acquiring individuals at the population
level. We find that this counterintuitive result is a consequence of phage-host
population dynamics, in which restriction-modification systems delay infection
onset until bacteria reach densities at which the probability of lysogeny increases.
These results underscore the importance of population-level dynamics as a key
factor modulating costs and benefits of immunity to temperate bacteriophages
article_processing_charge: No
author:
- first_name: Maros
full_name: Pleska, Maros
id: 4569785E-F248-11E8-B48F-1D18A9856A87
last_name: Pleska
orcid: 0000-0001-7460-7479
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Dominik
full_name: Refardt, Dominik
last_name: Refardt
- first_name: Bruce
full_name: Levin, Bruce
last_name: Levin
- 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: Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics
promotes prophage acquisition in bacteria with innate immunity. Nature Ecology
and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z
apa: Pleska, M., Lang, M., Refardt, D., Levin, B., & Guet, C. C. (2018). Phage-host
population dynamics promotes prophage acquisition in bacteria with innate immunity.
Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0424-z
chicago: Pleska, Maros, Moritz Lang, Dominik Refardt, Bruce Levin, and Calin C Guet.
“Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with
Innate Immunity.” Nature Ecology and Evolution. Springer Nature, 2018.
https://doi.org/10.1038/s41559-017-0424-z.
ieee: M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population
dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature
Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018.
ista: Pleska M, Lang M, Refardt D, Levin B, Guet CC. 2018. Phage-host population
dynamics promotes prophage acquisition in bacteria with innate immunity. Nature
Ecology and Evolution. 2(2), 359–366.
mla: Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition
in Bacteria with Innate Immunity.” Nature Ecology and Evolution, vol. 2,
no. 2, Springer Nature, 2018, pp. 359–66, doi:10.1038/s41559-017-0424-z.
short: M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution
2 (2018) 359–366.
corr_author: '1'
date_created: 2018-12-11T11:46:35Z
date_published: 2018-02-01T00:00:00Z
date_updated: 2026-04-08T14:19:43Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41559-017-0424-z
ec_funded: 1
external_id:
isi:
- '000426516400027'
intvolume: ' 2'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa_version: None
page: 359 - 366
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 251BCBEC-B435-11E9-9278-68D0E5697425
grant_number: RGY0079/2011
name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification
Systems
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grant_number: '24210'
name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems
at the Single-Cell Level
publication: Nature Ecology and Evolution
publication_status: published
publisher: Springer Nature
publist_id: '7364'
quality_controlled: '1'
related_material:
record:
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relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Phage-host population dynamics promotes prophage acquisition in bacteria with
innate immunity
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2
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
orcid: 0000-0001-7777-546X
- 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: 2026-06-08T22:30:53Z
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'
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content_type: application/pdf
creator: dernst
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oa: 1
oa_version: Submitted Version
page: 1633 - 1643
project:
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call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2578D616-B435-11E9-9278-68D0E5697425
call_identifier: H2020
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name: Selective Barriers to Horizontal Gene Transfer
- _id: 251EE76E-B435-11E9-9278-68D0E5697425
grant_number: '24573'
name: Design principles underlying genetic switch architecture
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: '5585'
abstract:
- lang: eng
text: Mean repression values and standard error of the mean are given for all operator
mutant libraries.
article_processing_charge: No
author:
- first_name: Claudia
full_name: Igler, Claudia
id: 46613666-F248-11E8-B48F-1D18A9856A87
last_name: Igler
orcid: 0000-0001-7777-546X
- 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. Data for the paper Evolutionary
potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108
apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018).
Data for the paper Evolutionary potential of transcription factors for gene regulatory
rewiring. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:108
chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin
C Guet. “Data for the Paper Evolutionary Potential of Transcription Factors for
Gene Regulatory Rewiring.” Institute of Science and Technology Austria, 2018.
https://doi.org/10.15479/AT:ISTA:108.
ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Data for
the paper Evolutionary potential of transcription factors for gene regulatory
rewiring.” Institute of Science and Technology Austria, 2018.
ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Data for the paper
Evolutionary potential of transcription factors for gene regulatory rewiring,
Institute of Science and Technology Austria, 10.15479/AT:ISTA:108.
mla: Igler, Claudia, et al. Data for the Paper Evolutionary Potential of Transcription
Factors for Gene Regulatory Rewiring. Institute of Science and Technology
Austria, 2018, doi:10.15479/AT:ISTA:108.
short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, (2018).
datarep_id: '108'
date_created: 2018-12-12T12:31:40Z
date_published: 2018-07-20T00:00:00Z
date_updated: 2026-06-08T22:30:53Z
day: '20'
ddc:
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department:
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- _id: GaTk
doi: 10.15479/AT:ISTA:108
ec_funded: 1
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file_size: 16507
relation: main_file
file_date_updated: 2020-07-14T12:47:07Z
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month: '07'
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: 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
publisher: Institute of Science and Technology Austria
related_material:
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relation: research_paper
status: public
- id: '6371'
relation: research_paper
status: public
status: public
title: Data for the paper Evolutionary potential of transcription factors for gene
regulatory rewiring
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
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year: '2018'
...
---
_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: 2025-07-10T11:50:05Z
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
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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:
- 2041-1723
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
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: 2025-04-15T06:50:01Z
day: '01'
ddc:
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department:
- _id: CaGu
- _id: GaTk
doi: 10.1016/j.automatica.2017.03.030
ec_funded: 1
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isi:
- '000403513900006'
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content_type: application/pdf
creator: system
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isi: 1
language:
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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'
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quality_controlled: '1'
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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)
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type: journal_article
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volume: 81C
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
arxiv: 1
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. IOP Publishing. 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. IOP Publishing, 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. IOP Publishing, 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, IOP Publishing, 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: 2025-06-04T08:08:31Z
day: '26'
department:
- _id: GaTk
doi: 10.1088/1742-5468/aa85c3
ec_funded: 1
external_id:
arxiv:
- '1705.06303'
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:
- 1742-5468
publication_status: published
publisher: IOP Publishing
publist_id: '6826'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Phase transitions in integer linear problems
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2017
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.
corr_author: '1'
date_created: 2018-12-11T11:49:20Z
date_published: 2017-06-30T00:00:00Z
date_updated: 2025-07-10T12:01:45Z
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:
- 0036-8075
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 356
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
arxiv: 1
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: 2025-06-04T08:12:18Z
day: '10'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.96.010401
ec_funded: 1
external_id:
arxiv:
- '1703.00219'
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:
- 2470-0045
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 96
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
arxiv: 1
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: 2025-06-04T08:15:40Z
day: '28'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.95.062419
ec_funded: 1
external_id:
arxiv:
- '1703.00853'
isi:
- '000404546400004'
intvolume: ' 95'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1703.00853
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:
- 2470-0045
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 95
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: 2025-09-22T09:43:12Z
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'
...