---
_id: '5562'
abstract:
- lang: eng
  text: "This data was collected as part of the study [1]. It consists of preprocessed
    multi-electrode array recording from 160 salamander retinal ganglion cells responding
    to 297 repeats of a 19 s natural movie. The data is available in two formats:
    (1) a .mat file containing an array with dimensions “number of repeats” x “number
    of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data
    represented as an array with dimensions “number of neurons” x “number of samples”,
    where the number of samples is equal to the product of the number of repeats and
    timebins within a repeat. The time dimension is divided into 20 ms time windows,
    and the array is binary indicating whether a given cell elicited at least one
    spike in a given time window during a particular repeat. See the reference below
    for details regarding collection and preprocessing:\r\n\r\n[1] Tkačik G, Marre
    O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior
    in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408."
article_processing_charge: No
author:
- 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
- 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: Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode
    array recording from salamander retinal ganglion cells. 2017. doi:<a href="https://doi.org/10.15479/AT:ISTA:61">10.15479/AT:ISTA:61</a>
  apa: Marre, O., Tkačik, G., Amodei, D., Schneidman, E., Bialek, W., &#38; Berry,
    M. (2017). Multi-electrode array recording from salamander retinal ganglion cells.
    Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:61">https://doi.org/10.15479/AT:ISTA:61</a>
  chicago: Marre, Olivier, Gašper Tkačik, Dario Amodei, Elad Schneidman, William Bialek,
    and Michael Berry. “Multi-Electrode Array Recording from Salamander Retinal Ganglion
    Cells.” Institute of Science and Technology Austria, 2017. <a href="https://doi.org/10.15479/AT:ISTA:61">https://doi.org/10.15479/AT:ISTA:61</a>.
  ieee: O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Multi-electrode
    array recording from salamander retinal ganglion cells.” Institute of Science
    and Technology Austria, 2017.
  ista: Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode
    array recording from salamander retinal ganglion cells, Institute of Science and
    Technology Austria, <a href="https://doi.org/10.15479/AT:ISTA:61">10.15479/AT:ISTA:61</a>.
  mla: Marre, Olivier, et al. <i>Multi-Electrode Array Recording from Salamander Retinal
    Ganglion Cells</i>. Institute of Science and Technology Austria, 2017, doi:<a
    href="https://doi.org/10.15479/AT:ISTA:61">10.15479/AT:ISTA:61</a>.
  short: O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017).
datarep_id: '61'
date_created: 2018-12-12T12:31:33Z
date_published: 2017-02-27T00:00:00Z
date_updated: 2025-09-29T11:14:05Z
day: '27'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:61
file:
- access_level: open_access
  checksum: e620eff260646f57b479a69492c8b765
  content_type: application/octet-stream
  creator: system
  date_created: 2018-12-12T13:03:04Z
  date_updated: 2020-07-14T12:47:03Z
  file_id: '5622'
  file_name: IST-2017-61-v1+1_bint_fishmovie32_100.mat
  file_size: 1336936
  relation: main_file
- access_level: open_access
  checksum: de83f9b81ea0aae3cddfc3ed982e0759
  content_type: application/zip
  creator: system
  date_created: 2018-12-12T13:03:05Z
  date_updated: 2020-07-14T12:47:03Z
  file_id: '5623'
  file_name: IST-2017-61-v1+2_bint_fishmovie32_100.zip
  file_size: 1897543
  relation: main_file
file_date_updated: 2020-07-14T12:47:03Z
has_accepted_license: '1'
keyword:
- multi-electrode recording
- retinal ganglion cells
month: '02'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '2257'
    relation: used_in_publication
    status: public
status: public
title: Multi-electrode array recording from salamander retinal ganglion cells
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: '2017'
...
---
_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. <i>Nature Communications</i>.
    2017;8(1). doi:<a href="https://doi.org/10.1038/s41467-017-01683-1">10.1038/s41467-017-01683-1</a>
  apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., &#38; Guet, C. C. (2017).
    Shaping bacterial population behavior through computer interfaced control of individual
    cells. <i>Nature Communications</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/s41467-017-01683-1">https://doi.org/10.1038/s41467-017-01683-1</a>
  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.” <i>Nature Communications</i>. Nature Publishing Group, 2017.
    <a href="https://doi.org/10.1038/s41467-017-01683-1">https://doi.org/10.1038/s41467-017-01683-1</a>.
  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,” <i>Nature Communications</i>, 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.” <i>Nature Communications</i>, vol. 8,
    no. 1, 1535, Nature Publishing Group, 2017, doi:<a href="https://doi.org/10.1038/s41467-017-01683-1">10.1038/s41467-017-01683-1</a>.
  short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications
    8 (2017).
corr_author: '1'
date_created: 2018-12-11T11:47:30Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2025-09-11T07:34:12Z
day: '01'
ddc:
- '576'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41467-017-01683-1
ec_funded: 1
external_id:
  isi:
  - '000415323000008'
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'
isi: 1
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:
  - 2041-1723
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 8
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
arxiv: 1
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. <i>Scandinavian Journal of Statistics</i>. 2017;44(2):285-306.
    doi:<a href="https://doi.org/10.1111/sjos.12251">10.1111/sjos.12251</a>
  apa: Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., &#38; Uhler, C. (2017).
    Exact goodness-of-fit testing for the Ising model. <i>Scandinavian Journal of
    Statistics</i>. Wiley-Blackwell. <a href="https://doi.org/10.1111/sjos.12251">https://doi.org/10.1111/sjos.12251</a>
  chicago: Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline
    Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” <i>Scandinavian Journal
    of Statistics</i>. Wiley-Blackwell, 2017. <a href="https://doi.org/10.1111/sjos.12251">https://doi.org/10.1111/sjos.12251</a>.
  ieee: A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit
    testing for the Ising model,” <i>Scandinavian Journal of Statistics</i>, 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.” <i>Scandinavian Journal of Statistics</i>, vol. 44, no. 2, Wiley-Blackwell,
    2017, pp. 285–306, doi:<a href="https://doi.org/10.1111/sjos.12251">10.1111/sjos.12251</a>.
  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: 2026-04-08T13:55:45Z
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: '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) -&gt; u(t) + p, p in R) or scale-invariance (u(t) -&gt; pu(t), p in R&gt;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. <i>Automatica</i>.
    2017;81C:46-55. doi:<a href="https://doi.org/10.1016/j.automatica.2017.03.030">10.1016/j.automatica.2017.03.030</a>
  apa: Lang, M., &#38; Sontag, E. (2017). Zeros of nonlinear systems with input invariances.
    <i>Automatica</i>. International Federation of Automatic Control. <a href="https://doi.org/10.1016/j.automatica.2017.03.030">https://doi.org/10.1016/j.automatica.2017.03.030</a>
  chicago: Lang, Moritz, and Eduardo Sontag. “Zeros of Nonlinear Systems with Input
    Invariances.” <i>Automatica</i>. International Federation of Automatic Control,
    2017. <a href="https://doi.org/10.1016/j.automatica.2017.03.030">https://doi.org/10.1016/j.automatica.2017.03.030</a>.
  ieee: M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,”
    <i>Automatica</i>, 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.”
    <i>Automatica</i>, vol. 81C, International Federation of Automatic Control, 2017,
    pp. 46–55, doi:<a href="https://doi.org/10.1016/j.automatica.2017.03.030">10.1016/j.automatica.2017.03.030</a>.
  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:
- '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: '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. <i>Science</i>. 2017;356(6345):1379-1383.
    doi:<a href="https://doi.org/10.1126/science.aam5887">10.1126/science.aam5887</a>
  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. <i>Science</i>. American Association for the
    Advancement of Science. <a href="https://doi.org/10.1126/science.aam5887">https://doi.org/10.1126/science.aam5887</a>
  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.”
    <i>Science</i>. American Association for the Advancement of Science, 2017. <a
    href="https://doi.org/10.1126/science.aam5887">https://doi.org/10.1126/science.aam5887</a>.
  ieee: M. P. Zagórski <i>et al.</i>, “Decoding of position in the developing neural
    tube from antiparallel morphogen gradients,” <i>Science</i>, 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.” <i>Science</i>, vol. 356, no. 6345,
    American Association for the Advancement of Science, 2017, pp. 1379–83, doi:<a
    href="https://doi.org/10.1126/science.aam5887">10.1126/science.aam5887</a>.
  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:
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month: '06'
oa: 1
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page: 1379 - 1383
pmid: 1
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  name: Coordination of Patterning And Growth In the Spinal Cord
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  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
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  call_identifier: FP7
  grant_number: '201439'
  name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish
publication: Science
publication_identifier:
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publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '6474'
quality_controlled: '1'
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status: public
title: Decoding of position in the developing neural tube from antiparallel morphogen
  gradients
type: journal_article
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volume: 356
year: '2017'
...
---
_id: '955'
abstract:
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  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. <i>Nature Communications</i>. 2017;8(1).
    doi:<a href="https://doi.org/10.1038/s41467-017-00238-8">10.1038/s41467-017-00238-8</a>
  apa: Friedlander, T., Prizak, R., Barton, N. H., &#38; Tkačik, G. (2017). Evolution
    of new regulatory functions on biophysically realistic fitness landscapes. <i>Nature
    Communications</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/s41467-017-00238-8">https://doi.org/10.1038/s41467-017-00238-8</a>
  chicago: Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik.
    “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.”
    <i>Nature Communications</i>. Nature Publishing Group, 2017. <a href="https://doi.org/10.1038/s41467-017-00238-8">https://doi.org/10.1038/s41467-017-00238-8</a>.
  ieee: T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new
    regulatory functions on biophysically realistic fitness landscapes,” <i>Nature
    Communications</i>, 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.” <i>Nature Communications</i>, vol. 8, no. 1, 216,
    Nature Publishing Group, 2017, doi:<a href="https://doi.org/10.1038/s41467-017-00238-8">10.1038/s41467-017-00238-8</a>.
  short: T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications
    8 (2017).
corr_author: '1'
date_created: 2018-12-11T11:49:23Z
date_published: 2017-08-09T00:00:00Z
date_updated: 2026-04-08T13:54:24Z
day: '09'
ddc:
- '539'
- '576'
department:
- _id: GaTk
- _id: NiBa
doi: 10.1038/s41467-017-00238-8
ec_funded: 1
external_id:
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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
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  call_identifier: FWF
  grant_number: P28844-B27
  name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
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publisher: Nature Publishing Group
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title: Evolution of new regulatory functions on biophysically realistic fitness landscapes
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  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2017'
...
---
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abstract:
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  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:<a href="https://doi.org/10.5061/dryad.1f1rc">10.5061/dryad.1f1rc</a>'
  apa: 'Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., &#38; Berry, M.
    (2017). Data from: Error-robust modes of the retinal population code. Dryad. <a
    href="https://doi.org/10.5061/dryad.1f1rc">https://doi.org/10.5061/dryad.1f1rc</a>'
  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. <a href="https://doi.org/10.5061/dryad.1f1rc">https://doi.org/10.5061/dryad.1f1rc</a>.'
  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, <a href="https://doi.org/10.5061/dryad.1f1rc">10.5061/dryad.1f1rc</a>.'
  mla: 'Prentice, Jason, et al. <i>Data from: Error-Robust Modes of the Retinal Population
    Code</i>. Dryad, 2017, doi:<a href="https://doi.org/10.5061/dryad.1f1rc">10.5061/dryad.1f1rc</a>.'
  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:
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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: '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:<a href="https://doi.org/10.1109/DEVLRN.2016.7846789">10.1109/DEVLRN.2016.7846789</a>'
  apa: 'Der, R., &#38; 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. <a href="https://doi.org/10.1109/DEVLRN.2016.7846789">https://doi.org/10.1109/DEVLRN.2016.7846789</a>'
  chicago: Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral
    Development and Emergent Social Interactions in Robots.” IEEE, 2017. <a href="https://doi.org/10.1109/DEVLRN.2016.7846789">https://doi.org/10.1109/DEVLRN.2016.7846789</a>.
  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. <i>Dynamical Self Consistency Leads to Behavioral
    Development and Emergent Social Interactions in Robots</i>. 7846789, IEEE, 2017,
    doi:<a href="https://doi.org/10.1109/DEVLRN.2016.7846789">10.1109/DEVLRN.2016.7846789</a>.
  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 &quot;waiting&quot; 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.
    <i>Frontiers in Neurorobotics</i>. 2017;11(MAR). doi:<a href="https://doi.org/10.3389/fnbot.2017.00008">10.3389/fnbot.2017.00008</a>
  apa: Der, R., &#38; Martius, G. S. (2017). Self organized behavior generation for
    musculoskeletal robots. <i>Frontiers in Neurorobotics</i>. Frontiers Research
    Foundation. <a href="https://doi.org/10.3389/fnbot.2017.00008">https://doi.org/10.3389/fnbot.2017.00008</a>
  chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for
    Musculoskeletal Robots.” <i>Frontiers in Neurorobotics</i>. Frontiers Research
    Foundation, 2017. <a href="https://doi.org/10.3389/fnbot.2017.00008">https://doi.org/10.3389/fnbot.2017.00008</a>.
  ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal
    robots,” <i>Frontiers in Neurorobotics</i>, 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.” <i>Frontiers in Neurorobotics</i>, vol. 11, no. MAR, 00008, Frontiers
    Research Foundation, 2017, doi:<a href="https://doi.org/10.3389/fnbot.2017.00008">10.3389/fnbot.2017.00008</a>.
  short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).
corr_author: '1'
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2025-09-11T07:10:33Z
day: '16'
ddc:
- '006'
department:
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- _id: GaTk
doi: 10.3389/fnbot.2017.00008
ec_funded: 1
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  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
publication: Frontiers in Neurorobotics
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  issn:
  - 1662-5218
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '7078'
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scopus_import: '1'
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title: Self organized behavior generation for musculoskeletal robots
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type: journal_article
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volume: 11
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. <i>Science</i>.
    2017;356(6335):311-315. doi:<a href="https://doi.org/10.1126/science.aaf4762">10.1126/science.aaf4762</a>
  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. <i>Science</i>. American Association
    for the Advancement of Science. <a href="https://doi.org/10.1126/science.aaf4762">https://doi.org/10.1126/science.aaf4762</a>
  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.”
    <i>Science</i>. American Association for the Advancement of Science, 2017. <a
    href="https://doi.org/10.1126/science.aaf4762">https://doi.org/10.1126/science.aaf4762</a>.
  ieee: T. Bergmiller <i>et al.</i>, “Biased partitioning of the multidrug efflux
    pump AcrAB TolC underlies long lived phenotypic heterogeneity,” <i>Science</i>,
    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.” <i>Science</i>, vol.
    356, no. 6335, American Association for the Advancement of Science, 2017, pp.
    311–15, doi:<a href="https://doi.org/10.1126/science.aaf4762">10.1126/science.aaf4762</a>.
  short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild,
    G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.
corr_author: '1'
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-21T00:00:00Z
date_updated: 2025-09-11T07:05:04Z
day: '21'
department:
- _id: CaGu
- _id: GaTk
- _id: Bio
doi: 10.1126/science.aaf4762
external_id:
  isi:
  - '000399540100060'
intvolume: '       356'
isi: 1
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:
  - 0036-8075
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 356
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. <i>Cell Systems</i>.
    2017;4(4):393-403. doi:<a href="https://doi.org/10.1016/j.cels.2017.03.001">10.1016/j.cels.2017.03.001</a>
  apa: Mitosch, K., Rieckh, G., &#38; Bollenbach, M. T. (2017). Noisy response to
    antibiotic stress predicts subsequent single cell survival in an acidic environment.
    <i>Cell Systems</i>. Cell Press. <a href="https://doi.org/10.1016/j.cels.2017.03.001">https://doi.org/10.1016/j.cels.2017.03.001</a>
  chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response
    to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.”
    <i>Cell Systems</i>. Cell Press, 2017. <a href="https://doi.org/10.1016/j.cels.2017.03.001">https://doi.org/10.1016/j.cels.2017.03.001</a>.
  ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic
    stress predicts subsequent single cell survival in an acidic environment,” <i>Cell
    Systems</i>, 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.” <i>Cell Systems</i>, vol. 4, no.
    4, Cell Press, 2017, pp. 393–403, doi:<a href="https://doi.org/10.1016/j.cels.2017.03.001">10.1016/j.cels.2017.03.001</a>.
  short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.
corr_author: '1'
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-26T00:00:00Z
date_updated: 2026-04-08T14:21:56Z
day: '26'
ddc:
- '576'
- '610'
department:
- _id: ToBo
- _id: GaTk
doi: 10.1016/j.cels.2017.03.001
ec_funded: 1
external_id:
  isi:
  - '000402747300005'
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'
isi: 1
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:
  - 2405-4712
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:
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  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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 4
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
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. Sensory noise predicts divisive reshaping
    of receptive fields. <i>PLoS Computational Biology</i>. 2017;13(6). doi:<a href="https://doi.org/10.1371/journal.pcbi.1005582">10.1371/journal.pcbi.1005582</a>
  apa: Chalk, M. J., Masset, P., Gutkin, B., &#38; Denève, S. (2017). Sensory noise
    predicts divisive reshaping of receptive fields. <i>PLoS Computational Biology</i>.
    Public Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1005582">https://doi.org/10.1371/journal.pcbi.1005582</a>
  chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory
    Noise Predicts Divisive Reshaping of Receptive Fields.” <i>PLoS Computational
    Biology</i>. Public Library of Science, 2017. <a href="https://doi.org/10.1371/journal.pcbi.1005582">https://doi.org/10.1371/journal.pcbi.1005582</a>.
  ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts
    divisive reshaping of receptive fields,” <i>PLoS Computational Biology</i>, 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.” <i>PLoS Computational Biology</i>, vol. 13, no. 6, e1005582, Public Library
    of Science, 2017, doi:<a href="https://doi.org/10.1371/journal.pcbi.1005582">10.1371/journal.pcbi.1005582</a>.
  short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13
    (2017).
corr_author: '1'
date_created: 2018-12-11T11:47:53Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2025-09-10T14:20:48Z
day: '01'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005582
external_id:
  isi:
  - '000404565400034'
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'
isi: 1
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
  issn:
  - 1553-734X
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 13
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. <i>PLoS Computational Biology</i>. 2017;13(9).
    doi:<a href="https://doi.org/10.1371/journal.pcbi.1005763">10.1371/journal.pcbi.1005763</a>
  apa: Humplik, J., &#38; Tkačik, G. (2017). Probabilistic models for neural populations
    that naturally capture global coupling and criticality. <i>PLoS Computational
    Biology</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1005763">https://doi.org/10.1371/journal.pcbi.1005763</a>
  chicago: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations
    That Naturally Capture Global Coupling and Criticality.” <i>PLoS Computational
    Biology</i>. Public Library of Science, 2017. <a href="https://doi.org/10.1371/journal.pcbi.1005763">https://doi.org/10.1371/journal.pcbi.1005763</a>.
  ieee: J. Humplik and G. Tkačik, “Probabilistic models for neural populations that
    naturally capture global coupling and criticality,” <i>PLoS Computational Biology</i>,
    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.” <i>PLoS Computational
    Biology</i>, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:<a
    href="https://doi.org/10.1371/journal.pcbi.1005763">10.1371/journal.pcbi.1005763</a>.
  short: J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017).
corr_author: '1'
date_created: 2018-12-11T11:48:08Z
date_published: 2017-09-19T00:00:00Z
date_updated: 2025-09-10T10:58:42Z
day: '19'
ddc:
- '530'
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005763
external_id:
  isi:
  - '000411981000042'
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'
isi: 1
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:
  - 1553-734X
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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.
article_processing_charge: No
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. <i>PNAS</i>. 2017;114(38):10149-10154.
    doi:<a href="https://doi.org/10.1073/pnas.1703817114">10.1073/pnas.1703817114</a>
  apa: Harpaz, R., Tkačik, G., &#38; Schneidman, E. (2017). Discrete modes of social
    information processing predict individual behavior of fish in a group. <i>PNAS</i>.
    National Academy of Sciences. <a href="https://doi.org/10.1073/pnas.1703817114">https://doi.org/10.1073/pnas.1703817114</a>
  chicago: Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social
    Information Processing Predict Individual Behavior of Fish in a Group.” <i>PNAS</i>.
    National Academy of Sciences, 2017. <a href="https://doi.org/10.1073/pnas.1703817114">https://doi.org/10.1073/pnas.1703817114</a>.
  ieee: R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information
    processing predict individual behavior of fish in a group,” <i>PNAS</i>, 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.” <i>PNAS</i>, vol. 114, no. 38, National
    Academy of Sciences, 2017, pp. 10149–54, doi:<a href="https://doi.org/10.1073/pnas.1703817114">10.1073/pnas.1703817114</a>.
  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: 2025-09-10T10:53:06Z
day: '19'
department:
- _id: GaTk
doi: 10.1073/pnas.1703817114
external_id:
  isi:
  - '000411157100063'
  pmid:
  - '28874581'
intvolume: '       114'
isi: 1
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:
  - 0027-8424
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 114
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. <i>Current Opinion in Neurobiology</i>. 2017;46:120-126. doi:<a href="https://doi.org/10.1016/j.conb.2017.08.001">10.1016/j.conb.2017.08.001</a>
  apa: Savin, C., &#38; Tkačik, G. (2017). Maximum entropy models as a tool for building
    precise neural controls. <i>Current Opinion in Neurobiology</i>. Elsevier. <a
    href="https://doi.org/10.1016/j.conb.2017.08.001">https://doi.org/10.1016/j.conb.2017.08.001</a>
  chicago: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for
    Building Precise Neural Controls.” <i>Current Opinion in Neurobiology</i>. Elsevier,
    2017. <a href="https://doi.org/10.1016/j.conb.2017.08.001">https://doi.org/10.1016/j.conb.2017.08.001</a>.
  ieee: C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise
    neural controls,” <i>Current Opinion in Neurobiology</i>, 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.” <i>Current Opinion in Neurobiology</i>, vol. 46, Elsevier,
    2017, pp. 120–26, doi:<a href="https://doi.org/10.1016/j.conb.2017.08.001">10.1016/j.conb.2017.08.001</a>.
  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: 2026-04-16T10:04:15Z
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:
  - 0959-4388
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: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 46
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:<a
    href="https://doi.org/10.1371/journal.pcbi.1005582.s001">10.1371/journal.pcbi.1005582.s001</a>
  apa: Chalk, M. J., Masset, P., Gutkin, B., &#38; Denève, S. (2017). Supplementary
    appendix. Public Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1005582.s001">https://doi.org/10.1371/journal.pcbi.1005582.s001</a>
  chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Supplementary
    Appendix.” Public Library of Science, 2017. <a href="https://doi.org/10.1371/journal.pcbi.1005582.s001">https://doi.org/10.1371/journal.pcbi.1005582.s001</a>.
  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, <a href="https://doi.org/10.1371/journal.pcbi.1005582.s001">10.1371/journal.pcbi.1005582.s001</a>.
  mla: Chalk, Matthew J., et al. <i>Supplementary Appendix</i>. Public Library of
    Science, 2017, doi:<a href="https://doi.org/10.1371/journal.pcbi.1005582.s001">10.1371/journal.pcbi.1005582.s001</a>.
  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: 2025-09-10T14:20:48Z
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: '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. <i>Nature Communications</i>.
    2017;8. doi:<a href="https://doi.org/10.1038/ncomms15140">10.1038/ncomms15140</a>
  apa: Levina (Martius), A., &#38; Priesemann, V. (2017). Subsampling scaling. <i>Nature
    Communications</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/ncomms15140">https://doi.org/10.1038/ncomms15140</a>
  chicago: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” <i>Nature
    Communications</i>. Nature Publishing Group, 2017. <a href="https://doi.org/10.1038/ncomms15140">https://doi.org/10.1038/ncomms15140</a>.
  ieee: A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” <i>Nature Communications</i>,
    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.” <i>Nature
    Communications</i>, vol. 8, 15140, Nature Publishing Group, 2017, doi:<a href="https://doi.org/10.1038/ncomms15140">10.1038/ncomms15140</a>.
  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: 2025-07-10T12:02:06Z
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:
  - 2041-1723
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
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. <i>Journal of Statistical Mechanics: Theory and Experiment</i>.
    2017;2017(9). doi:<a href="https://doi.org/10.1088/1742-5468/aa85c3">10.1088/1742-5468/aa85c3</a>'
  apa: 'Colabrese, S., De Martino, D., Leuzzi, L., &#38; Marinari, E. (2017). Phase
    transitions in integer linear problems. <i>Journal of Statistical Mechanics: Theory
    and Experiment</i>. IOP Publishing. <a href="https://doi.org/10.1088/1742-5468/aa85c3">https://doi.org/10.1088/1742-5468/aa85c3</a>'
  chicago: 'Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari.
    “Phase Transitions in Integer Linear Problems.” <i>Journal of Statistical Mechanics:
    Theory and Experiment</i>. IOP Publishing, 2017. <a href="https://doi.org/10.1088/1742-5468/aa85c3">https://doi.org/10.1088/1742-5468/aa85c3</a>.'
  ieee: 'S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions
    in integer linear problems,” <i>Journal of Statistical Mechanics: Theory and Experiment</i>,
    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.”
    <i>Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2017, no.
    9, 093404, IOP Publishing, 2017, doi:<a href="https://doi.org/10.1088/1742-5468/aa85c3">10.1088/1742-5468/aa85c3</a>.'
  short: 'S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical
    Mechanics: Theory and Experiment 2017 (2017).'
das_tickbox: '1'
date_created: 2018-12-11T11:48:41Z
date_published: 2017-09-26T00:00:00Z
date_updated: 2026-07-07T13:11:04Z
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: '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. <i>Physical Review E</i>. 2017;96(1). doi:<a href="https://doi.org/10.1103/PhysRevE.96.010401">10.1103/PhysRevE.96.010401</a>
  apa: De Martino, D., Capuani, F., &#38; De Martino, A. (2017). Quantifying the entropic
    cost of cellular growth control. <i>Physical Review E</i>. American Institute
    of Physics. <a href="https://doi.org/10.1103/PhysRevE.96.010401">https://doi.org/10.1103/PhysRevE.96.010401</a>
  chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying
    the Entropic Cost of Cellular Growth Control.” <i>Physical Review E</i>. American
    Institute of Physics, 2017. <a href="https://doi.org/10.1103/PhysRevE.96.010401">https://doi.org/10.1103/PhysRevE.96.010401</a>.
  ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost
    of cellular growth control,” <i>Physical Review E</i>, 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. 96(1), 010401.
  mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth
    Control.” <i>Physical Review E</i>, vol. 96, no. 1, 010401, American Institute
    of Physics, 2017, doi:<a href="https://doi.org/10.1103/PhysRevE.96.010401">10.1103/PhysRevE.96.010401</a>.
  short: D. De Martino, F. Capuani, A. De Martino, Physical Review E 96 (2017).
das_tickbox: '1'
date_created: 2018-12-11T11:49:21Z
date_published: 2017-07-10T00:00:00Z
date_updated: 2026-07-07T13:17:59Z
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
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. <i>Physical Review E</i>. 2017;95(6):062419.
    doi:<a href="https://doi.org/10.1103/PhysRevE.95.062419">10.1103/PhysRevE.95.062419</a>
  apa: De Martino, D. (2017). Scales and multimodal flux distributions in stationary
    metabolic network models via thermodynamics. <i>Physical Review E</i>. American
    Institute of Physics. <a href="https://doi.org/10.1103/PhysRevE.95.062419">https://doi.org/10.1103/PhysRevE.95.062419</a>
  chicago: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary
    Metabolic Network Models via Thermodynamics.” <i>Physical Review E</i>. American
    Institute of Physics, 2017. <a href="https://doi.org/10.1103/PhysRevE.95.062419">https://doi.org/10.1103/PhysRevE.95.062419</a>.
  ieee: D. De Martino, “Scales and multimodal flux distributions in stationary metabolic
    network models via thermodynamics,” <i>Physical Review E</i>, 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. 95(6), 062419.
  mla: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary
    Metabolic Network Models via Thermodynamics.” <i>Physical Review E</i>, vol. 95,
    no. 6, American Institute of Physics, 2017, p. 062419, doi:<a href="https://doi.org/10.1103/PhysRevE.95.062419">10.1103/PhysRevE.95.062419</a>.
  short: D. De Martino, Physical Review E 95 (2017) 062419.
das_tickbox: '1'
date_created: 2018-12-11T11:49:25Z
date_published: 2017-06-28T00:00:00Z
date_updated: 2026-07-07T13:19:44Z
day: '28'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.95.062419
ec_funded: 1
external_id:
  arxiv:
  - '1703.00853'
  isi:
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intvolume: '        95'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
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  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
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'
...
