---
_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: 2023-09-15T12:06:18Z
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).
date_created: 2018-12-11T11:46:18Z
date_published: 2018-03-07T00:00:00Z
date_updated: 2023-09-15T12:06:19Z
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: '1104'
abstract:
- lang: eng
text: In the early visual system, cells of the same type perform the same computation
in different places of the visual field. How these cells code together a complex
visual scene is unclear. A common assumption is that cells of a single-type extract
a single-stimulus feature to form a feature map, but this has rarely been observed
directly. Using large-scale recordings in the rat retina, we show that a homogeneous
population of fast OFF ganglion cells simultaneously encodes two radically different
features of a visual scene. Cells close to a moving object code quasilinearly
for its position, while distant cells remain largely invariant to the object's
position and, instead, respond nonlinearly to changes in the object's speed. We
develop a quantitative model that accounts for this effect and identify a disinhibitory
circuit that mediates it. Ganglion cells of a single type thus do not code for
one, but two features simultaneously. This richer, flexible neural map might also
be present in other sensory systems.
article_number: '1964'
article_processing_charge: No
author:
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Ulisse
full_name: Ferrari, Ulisse
last_name: Ferrari
- first_name: Emilie
full_name: Mace, Emilie
last_name: Mace
- first_name: Pierre
full_name: Yger, Pierre
last_name: Yger
- first_name: Romain
full_name: Caplette, Romain
last_name: Caplette
- first_name: Serge
full_name: Picaud, Serge
last_name: Picaud
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
citation:
ama: Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion
cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y
apa: Deny, S., Ferrari, U., Mace, E., Yger, P., Caplette, R., Picaud, S., … Marre,
O. (2017). Multiplexed computations in retinal ganglion cells of a single type.
Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-02159-y
chicago: Deny, Stephane, Ulisse Ferrari, Emilie Mace, Pierre Yger, Romain Caplette,
Serge Picaud, Gašper Tkačik, and Olivier Marre. “Multiplexed Computations in Retinal
Ganglion Cells of a Single Type.” Nature Communications. Nature Publishing
Group, 2017. https://doi.org/10.1038/s41467-017-02159-y.
ieee: S. Deny et al., “Multiplexed computations in retinal ganglion cells
of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing
Group, 2017.
ista: Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkačik G, Marre O.
2017. Multiplexed computations in retinal ganglion cells of a single type. Nature
Communications. 8(1), 1964.
mla: Deny, Stephane, et al. “Multiplexed Computations in Retinal Ganglion Cells
of a Single Type.” Nature Communications, vol. 8, no. 1, 1964, Nature Publishing
Group, 2017, doi:10.1038/s41467-017-02159-y.
short: S. Deny, U. Ferrari, E. Mace, P. Yger, R. Caplette, S. Picaud, G. Tkačik,
O. Marre, Nature Communications 8 (2017).
date_created: 2018-12-11T11:50:10Z
date_published: 2017-12-06T00:00:00Z
date_updated: 2023-09-20T11:41:19Z
day: '06'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1038/s41467-017-02159-y
ec_funded: 1
external_id:
isi:
- '000417241200004'
file:
- access_level: open_access
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:06Z
date_updated: 2018-12-12T10:16:06Z
file_id: '5191'
file_name: IST-2018-921-v1+1_s41467-017-02159-y.pdf
file_size: 2872887
relation: main_file
file_date_updated: 2018-12-12T10:16:06Z
has_accepted_license: '1'
intvolume: ' 8'
isi: 1
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25CD3DD2-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '604102'
name: Localization of ion channels and receptors by two and three-dimensional immunoelectron
microscopic approaches
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '6266'
pubrep_id: '921'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multiplexed computations in retinal ganglion cells of a single type
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 8
year: '2017'
...
---
_id: '823'
abstract:
- lang: eng
text: The resolution of a linear system with positive integer variables is a basic
yet difficult computational problem with many applications. We consider sparse
uncorrelated random systems parametrised by the density c and the ratio α=N/M
between number of variables N and number of constraints M. By means of ensemble
calculations we show that the space of feasible solutions endows a Van-Der-Waals
phase diagram in the plane (c, α). We give numerical evidence that the associated
computational problems become more difficult across the critical point and in
particular in the coexistence region.
article_number: '093404'
article_processing_charge: No
author:
- first_name: Simona
full_name: Colabrese, Simona
last_name: Colabrese
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Luca
full_name: Leuzzi, Luca
last_name: Leuzzi
- first_name: Enzo
full_name: Marinari, Enzo
last_name: Marinari
citation:
ama: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer
linear problems. Journal of Statistical Mechanics: Theory and Experiment.
2017;2017(9). doi:10.1088/1742-5468/aa85c3'
apa: 'Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase
transitions in integer linear problems. Journal of Statistical Mechanics:
Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3'
chicago: 'Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari.
“Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics:
Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.'
ieee: 'S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions
in integer linear problems,” Journal of Statistical Mechanics: Theory and
Experiment, vol. 2017, no. 9. IOPscience, 2017.'
ista: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions
in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment.
2017(9), 093404.'
mla: 'Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.”
Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no.
9, 093404, IOPscience, 2017, doi:10.1088/1742-5468/aa85c3.'
short: 'S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical
Mechanics: Theory and Experiment 2017 (2017).'
date_created: 2018-12-11T11:48:41Z
date_published: 2017-09-26T00:00:00Z
date_updated: 2023-09-26T16:18:12Z
day: '26'
department:
- _id: GaTk
doi: 10.1088/1742-5468/aa85c3
ec_funded: 1
external_id:
isi:
- '000411842900001'
intvolume: ' 2017'
isi: 1
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1705.06303
month: '09'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Journal of Statistical Mechanics: Theory and Experiment'
publication_identifier:
issn:
- '17425468'
publication_status: published
publisher: IOPscience
publist_id: '6826'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Phase transitions in integer linear problems
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '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. Scandinavian Journal of Statistics. 2017;44(2):285-306.
doi:10.1111/sjos.12251
apa: Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., & Uhler, C. (2017).
Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of
Statistics. Wiley-Blackwell. https://doi.org/10.1111/sjos.12251
chicago: Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline
Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal
of Statistics. Wiley-Blackwell, 2017. https://doi.org/10.1111/sjos.12251.
ieee: A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit
testing for the Ising model,” Scandinavian Journal of Statistics, vol.
44, no. 2. Wiley-Blackwell, pp. 285–306, 2017.
ista: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit
testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306.
mla: Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for
the Ising Model.” Scandinavian Journal of Statistics, vol. 44, no. 2, Wiley-Blackwell,
2017, pp. 285–306, doi:10.1111/sjos.12251.
short: A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian
Journal of Statistics 44 (2017) 285–306.
date_created: 2018-12-11T11:55:13Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-09-19T15:13:27Z
day: '01'
department:
- _id: GaTk
doi: 10.1111/sjos.12251
external_id:
arxiv:
- '1410.1242'
isi:
- '000400985000001'
intvolume: ' 44'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1410.1242
month: '06'
oa: 1
oa_version: Preprint
page: 285 - 306
publication: Scandinavian Journal of Statistics
publication_identifier:
issn:
- '03036898'
publication_status: published
publisher: Wiley-Blackwell
publist_id: '5060'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Exact goodness-of-fit testing for the Ising model
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 44
year: '2017'
...
---
_id: '665'
abstract:
- lang: eng
text: The molecular mechanisms underlying phenotypic variation in isogenic bacterial
populations remain poorly understood.We report that AcrAB-TolC, the main multidrug
efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell
poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex
formation. Mother cells inheriting old poles are phenotypically distinct and display
increased drug efflux activity relative to daughters. Consequently, we find systematic
and long-lived growth differences between mother and daughter cells in the presence
of subinhibitory drug concentrations. A simple model for biased partitioning predicts
a population structure of long-lived and highly heterogeneous phenotypes. This
straightforward mechanism of generating sustained growth rate differences at subinhibitory
antibiotic concentrations has implications for understanding the emergence of
multidrug resistance in bacteria.
article_processing_charge: No
article_type: original
author:
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Anna M
full_name: Andersson, Anna M
id: 2B8A40DA-F248-11E8-B48F-1D18A9856A87
last_name: Andersson
orcid: 0000-0003-2912-6769
- first_name: Kathrin
full_name: Tomasek, Kathrin
id: 3AEC8556-F248-11E8-B48F-1D18A9856A87
last_name: Tomasek
orcid: 0000-0003-3768-877X
- first_name: Enrique
full_name: Balleza, Enrique
last_name: Balleza
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug
efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science.
2017;356(6335):311-315. doi:10.1126/science.aaf4762
apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild,
R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB
TolC underlies long lived phenotypic heterogeneity. Science. American Association
for the Advancement of Science. https://doi.org/10.1126/science.aaf4762
chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza,
Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning
of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aaf4762.
ieee: T. Bergmiller et al., “Biased partitioning of the multidrug efflux
pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science,
vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315,
2017.
ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik
G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC
underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.
mla: Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump
AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science, vol.
356, no. 6335, American Association for the Advancement of Science, 2017, pp.
311–15, doi:10.1126/science.aaf4762.
short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild,
G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-21T00:00:00Z
date_updated: 2024-02-21T13:49:00Z
day: '21'
department:
- _id: CaGu
- _id: GaTk
- _id: Bio
doi: 10.1126/science.aaf4762
intvolume: ' 356'
issue: '6335'
language:
- iso: eng
month: '04'
oa_version: None
page: 311 - 315
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7064'
quality_controlled: '1'
related_material:
record:
- id: '5560'
relation: popular_science
status: public
scopus_import: 1
status: public
title: Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long
lived phenotypic heterogeneity
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 356
year: '2017'
...
---
_id: '666'
abstract:
- lang: eng
text: Antibiotics elicit drastic changes in microbial gene expression, including
the induction of stress response genes. While certain stress responses are known
to “cross-protect” bacteria from other stressors, it is unclear whether cellular
responses to antibiotics have a similar protective role. By measuring the genome-wide
transcriptional response dynamics of Escherichia coli to four antibiotics, we
found that trimethoprim induces a rapid acid stress response that protects bacteria
from subsequent exposure to acid. Combining microfluidics with time-lapse imaging
to monitor survival and acid stress response in single cells revealed that the
noisy expression of the acid resistance operon gadBC correlates with single-cell
survival. Cells with higher gadBC expression following trimethoprim maintain higher
intracellular pH and survive the acid stress longer. The seemingly random single-cell
survival under acid stress can therefore be predicted from gadBC expression and
rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap
for identifying the molecular mechanisms of single-cell cross-protection between
antibiotics and other stressors.
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts
subsequent single cell survival in an acidic environment. Cell Systems.
2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001
apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to
antibiotic stress predicts subsequent single cell survival in an acidic environment.
Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001
chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response
to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.”
Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001.
ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic
stress predicts subsequent single cell survival in an acidic environment,” Cell
Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.
ista: Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress
predicts subsequent single cell survival in an acidic environment. Cell Systems.
4(4), 393–403.
mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent
Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no.
4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001.
short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-26T00:00:00Z
date_updated: 2023-09-07T12:00:25Z
day: '26'
ddc:
- '576'
- '610'
department:
- _id: ToBo
- _id: GaTk
doi: 10.1016/j.cels.2017.03.001
ec_funded: 1
file:
- access_level: open_access
checksum: 04ff20011c3d9a601c514aa999a5fe1a
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:54Z
date_updated: 2020-07-14T12:47:35Z
file_id: '5041'
file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf
file_size: 2438660
relation: main_file
file_date_updated: 2020-07-14T12:47:35Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: 393 - 403
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
issn:
- '24054712'
publication_status: published
publisher: Cell Press
publist_id: '7061'
pubrep_id: '901'
quality_controlled: '1'
related_material:
record:
- id: '818'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Noisy response to antibiotic stress predicts subsequent single cell survival
in an acidic environment
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2017'
...
---
_id: '680'
abstract:
- lang: eng
text: In order to respond reliably to specific features of their environment, sensory
neurons need to integrate multiple incoming noisy signals. Crucially, they also
need to compete for the interpretation of those signals with other neurons representing
similar features. The form that this competition should take depends critically
on the noise corrupting these signals. In this study we show that for the type
of noise commonly observed in sensory systems, whose variance scales with the
mean signal, sensory neurons should selectively divide their input signals by
their predictions, suppressing ambiguous cues while amplifying others. Any change
in the stimulus context alters which inputs are suppressed, leading to a deep
dynamic reshaping of neural receptive fields going far beyond simple surround
suppression. Paradoxically, these highly variable receptive fields go alongside
and are in fact required for an invariant representation of external sensory features.
In addition to offering a normative account of context-dependent changes in sensory
responses, perceptual inference in the presence of signal-dependent noise accounts
for ubiquitous features of sensory neurons such as divisive normalization, gain
control and contrast dependent temporal dynamics.
article_number: e1005582
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Paul
full_name: Masset, Paul
last_name: Masset
- first_name: Boris
full_name: Gutkin, Boris
last_name: Gutkin
- first_name: Sophie
full_name: Denève, Sophie
last_name: Denève
citation:
ama: Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping
of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582
apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Sensory noise
predicts divisive reshaping of receptive fields. PLoS Computational Biology.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582
chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory
Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational
Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.
ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts
divisive reshaping of receptive fields,” PLoS Computational Biology, vol.
13, no. 6. Public Library of Science, 2017.
ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive
reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582.
mla: Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive
Fields.” PLoS Computational Biology, vol. 13, no. 6, e1005582, Public Library
of Science, 2017, doi:10.1371/journal.pcbi.1005582.
short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13
(2017).
date_created: 2018-12-11T11:47:53Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2023-02-23T14:10:54Z
day: '01'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005582
file:
- access_level: open_access
checksum: 796a1026076af6f4405a47d985bc7b68
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:07:47Z
date_updated: 2020-07-14T12:47:40Z
file_id: '4645'
file_name: IST-2017-898-v1+1_journal.pcbi.1005582.pdf
file_size: 14555676
relation: main_file
file_date_updated: 2020-07-14T12:47:40Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '7035'
pubrep_id: '898'
quality_controlled: '1'
related_material:
record:
- id: '9855'
relation: research_data
status: public
scopus_import: 1
status: public
title: Sensory noise predicts divisive reshaping of receptive fields
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2017'
...
---
_id: '720'
abstract:
- lang: eng
text: 'Advances in multi-unit recordings pave the way for statistical modeling of
activity patterns in large neural populations. Recent studies have shown that
the summed activity of all neurons strongly shapes the population response. A
separate recent finding has been that neural populations also exhibit criticality,
an anomalously large dynamic range for the probabilities of different population
activity patterns. Motivated by these two observations, we introduce a class of
probabilistic models which takes into account the prior knowledge that the neural
population could be globally coupled and close to critical. These models consist
of an energy function which parametrizes interactions between small groups of
neurons, and an arbitrary positive, strictly increasing, and twice differentiable
function which maps the energy of a population pattern to its probability. We
show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an
accurate description of the activity of retinal ganglion cells which outperforms
previous models based on the summed activity of neurons; 2) prior knowledge that
the population is critical translates to prior expectations about the shape of
the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous
latent variable globally coupling the system whose distribution we can infer from
data. Our method is independent of the underlying system’s state space; hence,
it can be applied to other systems such as natural scenes or amino acid sequences
of proteins which are also known to exhibit criticality.'
article_number: e1005763
article_processing_charge: Yes
author:
- first_name: Jan
full_name: Humplik, Jan
id: 2E9627A8-F248-11E8-B48F-1D18A9856A87
last_name: Humplik
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Humplik J, Tkačik G. Probabilistic models for neural populations that naturally
capture global coupling and criticality. PLoS Computational Biology. 2017;13(9).
doi:10.1371/journal.pcbi.1005763
apa: Humplik, J., & Tkačik, G. (2017). Probabilistic models for neural populations
that naturally capture global coupling and criticality. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005763
chicago: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations
That Naturally Capture Global Coupling and Criticality.” PLoS Computational
Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005763.
ieee: J. Humplik and G. Tkačik, “Probabilistic models for neural populations that
naturally capture global coupling and criticality,” PLoS Computational Biology,
vol. 13, no. 9. Public Library of Science, 2017.
ista: Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that
naturally capture global coupling and criticality. PLoS Computational Biology.
13(9), e1005763.
mla: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations
That Naturally Capture Global Coupling and Criticality.” PLoS Computational
Biology, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005763.
short: J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017).
date_created: 2018-12-11T11:48:08Z
date_published: 2017-09-19T00:00:00Z
date_updated: 2021-01-12T08:12:21Z
day: '19'
ddc:
- '530'
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1005763
file:
- access_level: open_access
checksum: 81107096c19771c36ddbe6f0282a3acb
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:30Z
date_updated: 2020-07-14T12:47:53Z
file_id: '5352'
file_name: IST-2017-884-v1+1_journal.pcbi.1005763.pdf
file_size: 14167050
relation: main_file
file_date_updated: 2020-07-14T12:47:53Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '6960'
pubrep_id: '884'
quality_controlled: '1'
scopus_import: 1
status: public
title: Probabilistic models for neural populations that naturally capture global coupling
and criticality
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2017'
...
---
_id: '725'
abstract:
- lang: eng
text: Individual computations and social interactions underlying collective behavior
in groups of animals are of great ethological, behavioral, and theoretical interest.
While complex individual behaviors have successfully been parsed into small dictionaries
of stereotyped behavioral modes, studies of collective behavior largely ignored
these findings; instead, their focus was on inferring single, mode-independent
social interaction rules that reproduced macroscopic and often qualitative features
of group behavior. Here, we bring these two approaches together to predict individual
swimming patterns of adult zebrafish in a group. We show that fish alternate between
an “active” mode, in which they are sensitive to the swimming patterns of conspecifics,
and a “passive” mode, where they ignore them. Using a model that accounts for
these two modes explicitly, we predict behaviors of individual fish with high
accuracy, outperforming previous approaches that assumed a single continuous computation
by individuals and simple metric or topological weighing of neighbors’ behavior.
At the group level, switching between active and passive modes is uncorrelated
among fish, but correlated directional swimming behavior still emerges. Our quantitative
approach for studying complex, multi-modal individual behavior jointly with emergent
group behavior is readily extensible to additional behavioral modes and their
neural correlates as well as to other species.
author:
- first_name: Roy
full_name: Harpaz, Roy
last_name: Harpaz
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing
predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154.
doi:10.1073/pnas.1703817114
apa: Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social
information processing predict individual behavior of fish in a group. PNAS.
National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114
chicago: Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social
Information Processing Predict Individual Behavior of Fish in a Group.” PNAS.
National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114.
ieee: R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information
processing predict individual behavior of fish in a group,” PNAS, vol.
114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.
ista: Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information
processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154.
mla: Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict
Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National
Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114.
short: R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154.
date_created: 2018-12-11T11:48:10Z
date_published: 2017-09-19T00:00:00Z
date_updated: 2021-01-12T08:12:36Z
day: '19'
department:
- _id: GaTk
doi: 10.1073/pnas.1703817114
external_id:
pmid:
- '28874581'
intvolume: ' 114'
issue: '38'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/
month: '09'
oa: 1
oa_version: Submitted Version
page: 10149 - 10154
pmid: 1
publication: PNAS
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
publist_id: '6953'
quality_controlled: '1'
scopus_import: 1
status: public
title: Discrete modes of social information processing predict individual behavior
of fish in a group
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 114
year: '2017'
...
---
_id: '730'
abstract:
- lang: eng
text: Neural responses are highly structured, with population activity restricted
to a small subset of the astronomical range of possible activity patterns. Characterizing
these statistical regularities is important for understanding circuit computation,
but challenging in practice. Here we review recent approaches based on the maximum
entropy principle used for quantifying collective behavior in neural activity.
We highlight recent models that capture population-level statistics of neural
data, yielding insights into the organization of the neural code and its biological
substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing
surrogate ensembles that preserve aspects of the data, but are otherwise maximally
unstructured. This idea can be used to generate a hierarchy of controls against
which rigorous statistical tests are possible.
article_processing_charge: No
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural
controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001
apa: Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building
precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001
chicago: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for
Building Precise Neural Controls.” Current Opinion in Neurobiology. Elsevier,
2017. https://doi.org/10.1016/j.conb.2017.08.001.
ieee: C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise
neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp.
120–126, 2017.
ista: Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise
neural controls. Current Opinion in Neurobiology. 46, 120–126.
mla: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building
Precise Neural Controls.” Current Opinion in Neurobiology, vol. 46, Elsevier,
2017, pp. 120–26, doi:10.1016/j.conb.2017.08.001.
short: C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126.
date_created: 2018-12-11T11:48:11Z
date_published: 2017-10-01T00:00:00Z
date_updated: 2023-09-28T11:32:22Z
day: '01'
department:
- _id: GaTk
doi: 10.1016/j.conb.2017.08.001
ec_funded: 1
external_id:
isi:
- '000416196400016'
intvolume: ' 46'
isi: 1
language:
- iso: eng
month: '10'
oa_version: None
page: 120 - 126
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Current Opinion in Neurobiology
publication_identifier:
issn:
- '09594388'
publication_status: published
publisher: Elsevier
publist_id: '6943'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Maximum entropy models as a tool for building precise neural controls
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 46
year: '2017'
...
---
_id: '735'
abstract:
- lang: eng
text: Cell-cell contact formation constitutes an essential step in evolution, leading
to the differentiation of specialized cell types. However, remarkably little is
known about whether and how the interplay between contact formation and fate specification
affects development. Here, we identify a positive feedback loop between cell-cell
contact duration, morphogen signaling, and mesendoderm cell-fate specification
during zebrafish gastrulation. We show that long-lasting cell-cell contacts enhance
the competence of prechordal plate (ppl) progenitor cells to respond to Nodal
signaling, required for ppl cell-fate specification. We further show that Nodal
signaling promotes ppl cell-cell contact duration, generating a positive feedback
loop between ppl cell-cell contact duration and cell-fate specification. Finally,
by combining mathematical modeling and experimentation, we show that this feedback
determines whether anterior axial mesendoderm cells become ppl or, instead, turn
into endoderm. Thus, the interdependent activities of cell-cell signaling and
contact formation control fate diversification within the developing embryo.
article_processing_charge: No
author:
- first_name: Vanessa
full_name: Barone, Vanessa
id: 419EECCC-F248-11E8-B48F-1D18A9856A87
last_name: Barone
orcid: 0000-0003-2676-3367
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Gabriel
full_name: Krens, Gabriel
id: 2B819732-F248-11E8-B48F-1D18A9856A87
last_name: Krens
orcid: 0000-0003-4761-5996
- first_name: Saurabh
full_name: Pradhan, Saurabh
last_name: Pradhan
- first_name: Shayan
full_name: Shamipour, Shayan
id: 40B34FE2-F248-11E8-B48F-1D18A9856A87
last_name: Shamipour
- first_name: Keisuke
full_name: Sako, Keisuke
id: 3BED66BE-F248-11E8-B48F-1D18A9856A87
last_name: Sako
orcid: 0000-0002-6453-8075
- first_name: Mateusz K
full_name: Sikora, Mateusz K
id: 2F74BCDE-F248-11E8-B48F-1D18A9856A87
last_name: Sikora
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Carl-Philipp J
full_name: Heisenberg, Carl-Philipp J
id: 39427864-F248-11E8-B48F-1D18A9856A87
last_name: Heisenberg
orcid: 0000-0002-0912-4566
citation:
ama: Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell
contact duration and morphogen signaling determines cell fate. Developmental
Cell. 2017;43(2):198-211. doi:10.1016/j.devcel.2017.09.014
apa: Barone, V., Lang, M., Krens, G., Pradhan, S., Shamipour, S., Sako, K., … Heisenberg,
C.-P. J. (2017). An effective feedback loop between cell-cell contact duration
and morphogen signaling determines cell fate. Developmental Cell. Cell
Press. https://doi.org/10.1016/j.devcel.2017.09.014
chicago: Barone, Vanessa, Moritz Lang, Gabriel Krens, Saurabh Pradhan, Shayan Shamipour,
Keisuke Sako, Mateusz K Sikora, Calin C Guet, and Carl-Philipp J Heisenberg. “An
Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling
Determines Cell Fate.” Developmental Cell. Cell Press, 2017. https://doi.org/10.1016/j.devcel.2017.09.014.
ieee: V. Barone et al., “An effective feedback loop between cell-cell contact
duration and morphogen signaling determines cell fate,” Developmental Cell,
vol. 43, no. 2. Cell Press, pp. 198–211, 2017.
ista: Barone V, Lang M, Krens G, Pradhan S, Shamipour S, Sako K, Sikora MK, Guet
CC, Heisenberg C-PJ. 2017. An effective feedback loop between cell-cell contact
duration and morphogen signaling determines cell fate. Developmental Cell. 43(2),
198–211.
mla: Barone, Vanessa, et al. “An Effective Feedback Loop between Cell-Cell Contact
Duration and Morphogen Signaling Determines Cell Fate.” Developmental Cell,
vol. 43, no. 2, Cell Press, 2017, pp. 198–211, doi:10.1016/j.devcel.2017.09.014.
short: V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora,
C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211.
date_created: 2018-12-11T11:48:13Z
date_published: 2017-10-23T00:00:00Z
date_updated: 2024-03-25T23:30:21Z
day: '23'
department:
- _id: CaHe
- _id: CaGu
- _id: GaTk
doi: 10.1016/j.devcel.2017.09.014
ec_funded: 1
external_id:
isi:
- '000413443700011'
intvolume: ' 43'
isi: 1
issue: '2'
language:
- iso: eng
month: '10'
oa_version: None
page: 198 - 211
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 252DD2A6-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I2058
name: 'Cell segregation in gastrulation: the role of cell fate specification'
publication: Developmental Cell
publication_identifier:
issn:
- '15345807'
publication_status: published
publisher: Cell Press
publist_id: '6934'
quality_controlled: '1'
related_material:
record:
- id: '961'
relation: dissertation_contains
status: public
- id: '8350'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: An effective feedback loop between cell-cell contact duration and morphogen
signaling determines cell fate
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 43
year: '2017'
...
---
_id: '548'
abstract:
- lang: eng
text: In this work maximum entropy distributions in the space of steady states of
metabolic networks are considered upon constraining the first and second moments
of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux
distributions, emerges upon considering control on the average growth (optimization)
and its fluctuations (heterogeneity). This is applied to the carbon catabolic
core of Escherichia coli where it quantifies the metabolic activity of slow growing
phenotypes and it provides a quantitative map with metabolic fluxes, opening the
possibility to detect coexistence from flux data. A preliminary analysis on data
for E. coli cultures in standard conditions shows degeneracy for the inferred
parameters that extend in the coexistence region.
alternative_title:
- Rapid Communications
article_number: '060401'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: De Martino D. Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E.
2017;96(6). doi:10.1103/PhysRevE.96.060401
apa: De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E.
American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401
chicago: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by
Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical
Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401.
ieee: D. De Martino, “Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes,” Physical Review E,
vol. 96, no. 6. American Physical Society, 2017.
ista: De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining
growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6),
060401.
mla: De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining
Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E,
vol. 96, no. 6, 060401, American Physical Society, 2017, doi:10.1103/PhysRevE.96.060401.
short: D. De Martino, Physical Review E 96 (2017).
date_created: 2018-12-11T11:47:06Z
date_published: 2017-12-21T00:00:00Z
date_updated: 2023-10-10T13:29:38Z
day: '21'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.96.060401
ec_funded: 1
intvolume: ' 96'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1707.00320
month: '12'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Review E
publication_identifier:
issn:
- 2470-0045
publication_status: published
publisher: American Physical Society
publist_id: '7266'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Maximum entropy modeling of metabolic networks by constraining growth-rate
moments predicts coexistence of phenotypes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 96
year: '2017'
...
---
_id: '5560'
abstract:
- lang: eng
text: "This repository contains the data collected for the manuscript \"Biased partitioning
of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity\".\r\nThe
data is compressed into a single archive. Within the archive, different folders
correspond to figures of the main text and the SI of the related publication.\r\nData
is saved as plain text, with each folder containing a separate readme file describing
the format. Typically, the data is from fluorescence microscopy measurements of
single cells growing in a microfluidic \"mother machine\" device, and consists
of relevant values (primarily arbitrary unit or normalized fluorescence measurements,
and division times / growth rates) after raw microscopy images have been processed,
segmented, and their features extracted, as described in the methods section of
the related publication."
article_processing_charge: No
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 multi-drug
efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:10.15479/AT:ISTA:53
apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild,
R., … Guet, C. C. (2017). Biased partitioning of the multi-drug efflux pump AcrAB-TolC
underlies long-lived phenotypic heterogeneity. Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:53
chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza,
Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning
of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity.”
Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:53.
ieee: T. Bergmiller et al., “Biased partitioning of the multi-drug efflux
pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science
and Technology Austria, 2017.
ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik
G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC
underlies long-lived phenotypic heterogeneity, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:53.
mla: Bergmiller, Tobias, et al. Biased Partitioning of the Multi-Drug Efflux
Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity. Institute of
Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:53.
short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild,
G. Tkačik, C.C. Guet, (2017).
datarep_id: '53'
date_created: 2018-12-12T12:31:32Z
date_published: 2017-03-10T00:00:00Z
date_updated: 2024-02-21T13:49:00Z
day: '10'
ddc:
- '571'
department:
- _id: CaGu
- _id: GaTk
- _id: Bio
doi: 10.15479/AT:ISTA:53
file:
- access_level: open_access
checksum: d77859af757ac8025c50c7b12b52eaf3
content_type: application/zip
creator: system
date_created: 2018-12-12T13:02:38Z
date_updated: 2020-07-14T12:47:03Z
file_id: '5603'
file_name: IST-2017-53-v1+1_Data_MDE.zip
file_size: 6773204
relation: main_file
file_date_updated: 2020-07-14T12:47:03Z
has_accepted_license: '1'
keyword:
- single cell microscopy
- mother machine microfluidic device
- AcrAB-TolC pump
- multi-drug efflux
- Escherichia coli
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '03'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '665'
relation: research_paper
status: public
status: public
title: Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived
phenotypic heterogeneity
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: '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:10.15479/AT:ISTA:61
apa: 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. https://doi.org/10.15479/AT:ISTA:61
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. https://doi.org/10.15479/AT:ISTA:61.
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, 10.15479/AT:ISTA:61.
mla: Marre, Olivier, et al. Multi-Electrode Array Recording from Salamander Retinal
Ganglion Cells. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:61.
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: 2024-02-21T13:46:14Z
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: research_paper
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. Nature Communications.
2017;8(1). doi:10.1038/s41467-017-01683-1
apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017).
Shaping bacterial population behavior through computer interfaced control of individual
cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1
chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin
C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control
of Individual Cells.” Nature Communications. Nature Publishing Group, 2017.
https://doi.org/10.1038/s41467-017-01683-1.
ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping
bacterial population behavior through computer interfaced control of individual
cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group,
2017.
ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial
population behavior through computer interfaced control of individual cells. Nature
Communications. 8(1), 1535.
mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer
Interfaced Control of Individual Cells.” Nature Communications, vol. 8,
no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1.
short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications
8 (2017).
date_created: 2018-12-11T11:47:30Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2021-01-12T08:06:15Z
day: '01'
ddc:
- '576'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41467-017-01683-1
ec_funded: 1
file:
- access_level: open_access
checksum: 44bb5d0229926c23a9955d9fe0f9723f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:05Z
date_updated: 2020-07-14T12:47:20Z
file_id: '5190'
file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf
file_size: 1951699
relation: main_file
file_date_updated: 2020-07-14T12:47:20Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
issn:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '7191'
pubrep_id: '911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Shaping bacterial population behavior through computer interfaced control of
individual cells
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2017'
...
---
_id: '652'
abstract:
- lang: eng
text: 'We present an approach that enables robots to self-organize their sensorimotor
behavior from scratch without providing specific information about neither the
robot nor its environment. This is achieved by a simple neural control law that
increases the consistency between external sensor dynamics and internal neural
dynamics of the utterly simple controller. In this way, the embodiment and the
agent-environment coupling are the only source of individual development. We show
how an anthropomorphic tendon driven arm-shoulder system develops different behaviors
depending on that coupling. For instance: Given a bottle half-filled with water,
the arm starts to shake it, driven by the physical response of the water. When
attaching a brush, the arm can be manipulated into wiping a table, and when connected
to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said
to discover the affordances of the world. When allowing two (simulated) humanoid
robots to interact physically, they engage into a joint behavior development leading
to, for instance, spontaneous cooperation. More social effects are observed if
the robots can visually perceive each other. Although, as an observer, it is tempting
to attribute an apparent intentionality, there is nothing of the kind put in.
As a conclusion, we argue that emergent behavior may be much less rooted in explicit
intentions, internal motivations, or specific reward systems than is commonly
believed.'
article_number: '7846789'
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: 'Der R, Martius GS. Dynamical self consistency leads to behavioral development
and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789'
apa: 'Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to
behavioral development and emergent social interactions in robots. Presented at
the ICDL EpiRob: International Conference on Development and Learning and Epigenetic
Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789'
chicago: Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral
Development and Emergent Social Interactions in Robots.” IEEE, 2017. https://doi.org/10.1109/DEVLRN.2016.7846789.
ieee: 'R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral
development and emergent social interactions in robots,” presented at the ICDL
EpiRob: International Conference on Development and Learning and Epigenetic Robotics
, Cergy-Pontoise, France, 2017.'
ista: 'Der R, Martius GS. 2017. Dynamical self consistency leads to behavioral development
and emergent social interactions in robots. ICDL EpiRob: International Conference
on Development and Learning and Epigenetic Robotics , 7846789.'
mla: Der, Ralf, and Georg S. Martius. Dynamical Self Consistency Leads to Behavioral
Development and Emergent Social Interactions in Robots. 7846789, IEEE, 2017,
doi:10.1109/DEVLRN.2016.7846789.
short: R. Der, G.S. Martius, in:, IEEE, 2017.
conference:
end_date: 2016-09-22
location: Cergy-Pontoise, France
name: 'ICDL EpiRob: International Conference on Development and Learning and Epigenetic
Robotics '
start_date: 2016-09-19
date_created: 2018-12-11T11:47:43Z
date_published: 2017-02-07T00:00:00Z
date_updated: 2021-01-12T08:07:51Z
day: '07'
department:
- _id: ChLa
- _id: GaTk
doi: 10.1109/DEVLRN.2016.7846789
language:
- iso: eng
month: '02'
oa_version: None
publication_identifier:
isbn:
- 978-150905069-7
publication_status: published
publisher: IEEE
publist_id: '7100'
quality_controlled: '1'
scopus_import: 1
status: public
title: Dynamical self consistency leads to behavioral development and emergent social
interactions in robots
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '658'
abstract:
- lang: eng
text: 'With the accelerated development of robot technologies, control becomes one
of the central themes of research. In traditional approaches, the controller,
by its internal functionality, finds appropriate actions on the basis of specific
objectives for the task at hand. While very successful in many applications, self-organized
control schemes seem to be favored in large complex systems with unknown dynamics
or which are difficult to model. Reasons are the expected scalability, robustness,
and resilience of self-organizing systems. The paper presents a self-learning
neurocontroller based on extrinsic differential plasticity introduced recently,
applying it to an anthropomorphic musculoskeletal robot arm with attached objects
of unknown physical dynamics. The central finding of the paper is the following
effect: by the mere feedback through the internal dynamics of the object, the
robot is learning to relate each of the objects with a very specific sensorimotor
pattern. Specifically, an attached pendulum pilots the arm into a circular motion,
a half-filled bottle produces axis oriented shaking behavior, a wheel is getting
rotated, and wiping patterns emerge automatically in a table-plus-brush setting.
By these object-specific dynamical patterns, the robot may be said to recognize
the object''s identity, or in other words, it discovers dynamical affordances
of objects. Furthermore, when including hand coordinates obtained from a camera,
a dedicated hand-eye coordination self-organizes spontaneously. These phenomena
are discussed from a specific dynamical system perspective. Central is the dedicated
working regime at the border to instability with its potentially infinite reservoir
of (limit cycle) attractors "waiting" to be excited. Besides converging
toward one of these attractors, variate behavior is also arising from a self-induced
attractor morphing driven by the learning rule. We claim that experimental investigations
with this anthropomorphic, self-learning robot not only generate interesting and
potentially useful behaviors, but may also help to better understand what subjective
human muscle feelings are, how they can be rooted in sensorimotor patterns, and
how these concepts may feed back on robotics.'
article_number: '00008'
article_processing_charge: Yes
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots.
Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008
apa: Der, R., & Martius, G. S. (2017). Self organized behavior generation for
musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research
Foundation. https://doi.org/10.3389/fnbot.2017.00008
chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for
Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research
Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008.
ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal
robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research
Foundation, 2017.
ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal
robots. Frontiers in Neurorobotics. 11(MAR), 00008.
mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal
Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers
Research Foundation, 2017, doi:10.3389/fnbot.2017.00008.
short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2021-01-12T08:08:04Z
day: '16'
ddc:
- '006'
department:
- _id: ChLa
- _id: GaTk
doi: 10.3389/fnbot.2017.00008
ec_funded: 1
file:
- access_level: open_access
checksum: b1bc43f96d1df3313c03032c2a46388d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:49Z
date_updated: 2020-07-14T12:47:33Z
file_id: '5371'
file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf
file_size: 8439566
relation: main_file
file_date_updated: 2020-07-14T12:47:33Z
has_accepted_license: '1'
intvolume: ' 11'
issue: MAR
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Frontiers in Neurorobotics
publication_identifier:
issn:
- '16625218'
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '7078'
pubrep_id: '903'
quality_controlled: '1'
scopus_import: 1
status: public
title: Self organized behavior generation for musculoskeletal robots
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2017'
...
---
_id: '943'
abstract:
- lang: eng
text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel
morphogen gradients. To understand how these inputs are interpreted, we measured
morphogen signaling and target gene expression in mouse embryos and chick ex vivo
assays. From these data, we derived and validated a characteristic decoding map
that relates morphogen input to the positional identity of neural progenitors.
Analysis of the observed responses indicates that the underlying interpretation
strategy minimizes patterning errors in response to the joint input of noisy opposing
gradients. We reverse-engineered a transcriptional network that provides a mechanistic
basis for the observed cell fate decisions and accounts for the precision and
dynamics of pattern formation. Together, our data link opposing gradient dynamics
in a growing tissue to precise pattern formation.
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Yoji
full_name: Tabata, Yoji
last_name: Tabata
- first_name: Nathalie
full_name: Brandenberg, Nathalie
last_name: Brandenberg
- first_name: Matthias
full_name: Lutolf, Matthias
last_name: Lutolf
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
last_name: Bollenbach
- first_name: James
full_name: Briscoe, James
last_name: Briscoe
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing
neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383.
doi:10.1126/science.aam5887
apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach,
T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from
antiparallel morphogen gradients. Science. American Association for the
Advancement of Science. https://doi.org/10.1126/science.aam5887
chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf,
Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of
Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887.
ieee: M. P. Zagórski et al., “Decoding of position in the developing neural
tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345.
American Association for the Advancement of Science, pp. 1379–1383, 2017.
ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe
J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel
morphogen gradients. Science. 356(6345), 1379–1383.
mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural
Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345,
American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887.
short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach,
J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.
date_created: 2018-12-11T11:49:20Z
date_published: 2017-06-30T00:00:00Z
date_updated: 2023-09-26T15:38:05Z
day: '30'
department:
- _id: AnKi
- _id: GaTk
doi: 10.1126/science.aam5887
ec_funded: 1
external_id:
isi:
- '000404351500036'
pmid:
- '28663499'
intvolume: ' 356'
isi: 1
issue: '6345'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/
month: '06'
oa: 1
oa_version: Submitted Version
page: 1379 - 1383
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2524F500-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '201439'
name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '6474'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Decoding of position in the developing neural tube from antiparallel morphogen
gradients
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 356
year: '2017'
...
---
_id: '947'
abstract:
- lang: eng
text: Viewing the ways a living cell can organize its metabolism as the phase space
of a physical system, regulation can be seen as the ability to reduce the entropy
of that space by selecting specific cellular configurations that are, in some
sense, optimal. Here we quantify the amount of regulation required to control
a cell's growth rate by a maximum-entropy approach to the space of underlying
metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern
as described by genome-scale models. We link the mean growth rate achieved by
a population of cells to the minimal amount of metabolic regulation needed to
achieve it through a phase diagram that highlights how growth suppression can
be as costly (in regulatory terms) as growth enhancement. Moreover, we provide
an interpretation of the inverse temperature β controlling maximum-entropy distributions
based on the underlying growth dynamics. Specifically, we show that the asymptotic
value of β for a cell population can be expected to depend on (i) the carrying
capacity of the environment, (ii) the initial size of the colony, and (iii) the
probability distribution from which the inoculum was sampled. Results obtained
for E. coli and human cells are found to be remarkably consistent with empirical
evidence.
article_number: '010401'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Fabrizio
full_name: Capuani, Fabrizio
last_name: Capuani
- first_name: Andrea
full_name: De Martino, Andrea
last_name: De Martino
citation:
ama: De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular
growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics
. 2017;96(1). doi:10.1103/PhysRevE.96.010401
apa: De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic
cost of cellular growth control. Physical Review E Statistical Nonlinear and
Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401
chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying
the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical
Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401.
ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost
of cellular growth control,” Physical Review E Statistical Nonlinear and Soft
Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017.
ista: De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost
of cellular growth control. Physical Review E Statistical Nonlinear and Soft
Matter Physics . 96(1), 010401.
mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth
Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics
, vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401.
short: D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical
Nonlinear and Soft Matter Physics 96 (2017).
date_created: 2018-12-11T11:49:21Z
date_published: 2017-07-10T00:00:00Z
date_updated: 2023-09-22T10:03:50Z
day: '10'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.96.010401
ec_funded: 1
external_id:
isi:
- '000405194200002'
intvolume: ' 96'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1703.00219
month: '07'
oa: 1
oa_version: Submitted Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics '
publication_identifier:
issn:
- '24700045'
publication_status: published
publisher: American Institute of Physics
publist_id: '6470'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantifying the entropic cost of cellular growth control
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 96
year: '2017'
...