---
_id: '6071'
abstract:
- lang: eng
text: 'Transcription factors, by binding to specific sequences on the DNA, control
the precise spatio-temporal expression of genes inside a cell. However, this specificity
is limited, leading to frequent incorrect binding of transcription factors that
might have deleterious consequences on the cell. By constructing a biophysical
model of TF-DNA binding in the context of gene regulation, I will first explore
how regulatory constraints can strongly shape the distribution of a population
in sequence space. Then, by directly linking this to a picture of multiple types
of transcription factors performing their functions simultaneously inside the
cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions
between transcription factors and binding sites that lead to erroneous regulatory
states -- and understand the constraints this places on the design of regulatory
systems. I will then develop a generic theoretical framework to investigate the
coevolution of multiple transcription factors and multiple binding sites, in the
context of a gene regulatory network that performs a certain function. As a particular
tractable version of this problem, I will consider the evolution of two transcription
factors when they transmit upstream signals to downstream target genes. Specifically,
I will describe the evolutionary steady states and the evolutionary pathways involved,
along with their timescales, of a system that initially undergoes a transcription
factor duplication event. To connect this important theoretical model to the prominent
biological event of transcription factor duplication giving rise to paralogous
families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription
factors, a major family in humans, and focus on the patterns of evolution that
paralogs have undergone in their various protein domains in the recent past. '
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
citation:
ama: Prizak R. Coevolution of transcription factors and their binding sites in sequence
space. 2019. doi:10.15479/at:ista:th6071
apa: Prizak, R. (2019). Coevolution of transcription factors and their binding
sites in sequence space. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:th6071
chicago: Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding
Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/at:ista:th6071.
ieee: R. Prizak, “Coevolution of transcription factors and their binding sites in
sequence space,” Institute of Science and Technology Austria, 2019.
ista: Prizak R. 2019. Coevolution of transcription factors and their binding sites
in sequence space. Institute of Science and Technology Austria.
mla: Prizak, Roshan. Coevolution of Transcription Factors and Their Binding Sites
in Sequence Space. Institute of Science and Technology Austria, 2019, doi:10.15479/at:ista:th6071.
short: R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in
Sequence Space, Institute of Science and Technology Austria, 2019.
date_created: 2019-03-06T16:16:10Z
date_published: 2019-03-11T00:00:00Z
date_updated: 2025-05-28T11:57:05Z
day: '11'
ddc:
- '576'
degree_awarded: PhD
department:
- _id: GaTk
- _id: NiBa
doi: 10.15479/at:ista:th6071
file:
- access_level: open_access
checksum: e60a72de35d270b31f1a23d50f224ec0
content_type: application/pdf
creator: rprizak
date_created: 2019-03-06T16:05:07Z
date_updated: 2020-07-14T12:47:18Z
file_id: '6072'
file_name: Thesis_final_PDFA_RoshanPrizak.pdf
file_size: 20995465
relation: main_file
- access_level: closed
checksum: 67c2630333d05ebafef5f018863a8465
content_type: application/zip
creator: rprizak
date_created: 2019-03-06T16:09:39Z
date_updated: 2020-07-14T12:47:18Z
file_id: '6073'
file_name: thesis_v2_merge.zip
file_size: 85705272
relation: source_file
title: Latex files
file_date_updated: 2020-07-14T12:47:18Z
has_accepted_license: '1'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: '189'
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '1358'
relation: part_of_dissertation
status: public
- id: '955'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
title: Coevolution of transcription factors and their binding sites in sequence space
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2019'
...
---
_id: '6090'
abstract:
- lang: eng
text: Cells need to reliably sense external ligand concentrations to achieve various
biological functions such as chemotaxis or signaling. The molecular recognition
of ligands by surface receptors is degenerate in many systems, leading to crosstalk
between ligand-receptor pairs. Crosstalk is often thought of as a deviation from
optimal specific recognition, as the binding of noncognate ligands can interfere
with the detection of the receptor's cognate ligand, possibly leading to a false
triggering of a downstream signaling pathway. Here we quantify the optimal precision
of sensing the concentrations of multiple ligands by a collection of promiscuous
receptors. We demonstrate that crosstalk can improve precision in concentration
sensing and discrimination tasks. To achieve superior precision, the additional
information about ligand concentrations contained in short binding events of the
noncognate ligand should be exploited. We present a proofreading scheme to realize
an approximate estimation of multiple ligand concentrations that reaches a precision
close to the derived optimal bounds. Our results help rationalize the observed
ubiquity of receptor crosstalk in molecular sensing.
article_number: '022423'
article_processing_charge: No
author:
- first_name: Martín
full_name: Carballo-Pacheco, Martín
last_name: Carballo-Pacheco
- first_name: Jonathan
full_name: Desponds, Jonathan
last_name: Desponds
- first_name: Tatyana
full_name: Gavrilchenko, Tatyana
last_name: Gavrilchenko
- first_name: Andreas
full_name: Mayer, Andreas
last_name: Mayer
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Gautam
full_name: Reddy, Gautam
last_name: Reddy
- first_name: Ilya
full_name: Nemenman, Ilya
last_name: Nemenman
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
citation:
ama: Carballo-Pacheco M, Desponds J, Gavrilchenko T, et al. Receptor crosstalk improves
concentration sensing of multiple ligands. Physical Review E. 2019;99(2).
doi:10.1103/PhysRevE.99.022423
apa: Carballo-Pacheco, M., Desponds, J., Gavrilchenko, T., Mayer, A., Prizak, R.,
Reddy, G., … Mora, T. (2019). Receptor crosstalk improves concentration sensing
of multiple ligands. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.99.022423
chicago: Carballo-Pacheco, Martín, Jonathan Desponds, Tatyana Gavrilchenko, Andreas
Mayer, Roshan Prizak, Gautam Reddy, Ilya Nemenman, and Thierry Mora. “Receptor
Crosstalk Improves Concentration Sensing of Multiple Ligands.” Physical Review
E. American Physical Society, 2019. https://doi.org/10.1103/PhysRevE.99.022423.
ieee: M. Carballo-Pacheco et al., “Receptor crosstalk improves concentration
sensing of multiple ligands,” Physical Review E, vol. 99, no. 2. American
Physical Society, 2019.
ista: Carballo-Pacheco M, Desponds J, Gavrilchenko T, Mayer A, Prizak R, Reddy G,
Nemenman I, Mora T. 2019. Receptor crosstalk improves concentration sensing of
multiple ligands. Physical Review E. 99(2), 022423.
mla: Carballo-Pacheco, Martín, et al. “Receptor Crosstalk Improves Concentration
Sensing of Multiple Ligands.” Physical Review E, vol. 99, no. 2, 022423,
American Physical Society, 2019, doi:10.1103/PhysRevE.99.022423.
short: M. Carballo-Pacheco, J. Desponds, T. Gavrilchenko, A. Mayer, R. Prizak, G.
Reddy, I. Nemenman, T. Mora, Physical Review E 99 (2019).
date_created: 2019-03-10T22:59:20Z
date_published: 2019-02-26T00:00:00Z
date_updated: 2024-02-28T13:12:06Z
day: '26'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1103/PhysRevE.99.022423
external_id:
isi:
- '000459916500007'
intvolume: ' 99'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/10.1101/448118v1.abstract
month: '02'
oa: 1
oa_version: Preprint
publication: Physical Review E
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Receptor crosstalk improves concentration sensing of multiple ligands
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 99
year: '2019'
...
---
_id: '6473'
abstract:
- lang: eng
text: "Single cells are constantly interacting with their environment and each other,
more importantly, the accurate perception of environmental cues is crucial for
growth, survival, and reproduction. This communication between cells and their
environment can be formalized in mathematical terms and be quantified as the information
flow between them, as prescribed by information theory. \r\nThe recent availability
of real–time dynamical patterns of signaling molecules in single cells has allowed
us to identify encoding about the identity of the environment in the time–series.
However, efficient estimation of the information transmitted by these signals
has been a data–analysis challenge due to the high dimensionality of the trajectories
and the limited number of samples. In the first part of this thesis, we develop
and evaluate decoding–based estimation methods to lower bound the mutual information
and derive model–based precise information estimates for biological reaction networks
governed by the chemical master equation. This is followed by applying the decoding-based
methods to study the intracellular representation of extracellular changes in
budding yeast, by observing the transient dynamics of nuclear translocation of
10 transcription factors in response to 3 stress conditions. Additionally, we
apply these estimators to previously published data on ERK and Ca2+ signaling
and yeast stress response. We argue that this single cell decoding-based measure
of information provides an unbiased, quantitative and interpretable measure for
the fidelity of biological signaling processes. \r\nFinally, in the last section,
we deal with gene regulation which is primarily controlled by transcription factors
(TFs) that bind to the DNA to activate gene expression. The possibility that non-cognate
TFs activate transcription diminishes the accuracy of regulation with potentially
disastrous effects for the cell. This ’crosstalk’ acts as a previously unexplored
source of noise in biochemical networks and puts a strong constraint on their
performance. To mitigate erroneous initiation we propose an out of equilibrium
scheme that implements kinetic proofreading. We show that such architectures are
favored over their equilibrium counterparts for complex organisms despite introducing
noise in gene expression. "
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
citation:
ama: Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:10.15479/AT:ISTA:6473
apa: Cepeda Humerez, S. A. (2019). Estimating information flow in single cells.
Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:6473
chicago: Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.”
Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/AT:ISTA:6473.
ieee: S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute
of Science and Technology Austria, 2019.
ista: Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute
of Science and Technology Austria.
mla: Cepeda Humerez, Sarah A. Estimating Information Flow in Single Cells.
Institute of Science and Technology Austria, 2019, doi:10.15479/AT:ISTA:6473.
short: S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute
of Science and Technology Austria, 2019.
date_created: 2019-05-21T00:11:23Z
date_published: 2019-05-23T00:00:00Z
date_updated: 2025-05-28T11:57:00Z
day: '23'
ddc:
- '004'
degree_awarded: PhD
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:6473
file:
- access_level: closed
checksum: 75f9184c1346e10a5de5f9cc7338309a
content_type: application/zip
creator: scepeda
date_created: 2019-05-23T11:18:16Z
date_updated: 2020-07-14T12:47:31Z
file_id: '6480'
file_name: Thesis_Cepeda.zip
file_size: 23937464
relation: source_file
- access_level: open_access
checksum: afdc0633ddbd71d5b13550d7fb4f4454
content_type: application/pdf
creator: scepeda
date_created: 2019-05-23T11:18:13Z
date_updated: 2020-07-14T12:47:31Z
file_id: '6481'
file_name: CepedaThesis.pdf
file_size: 16646985
relation: main_file
file_date_updated: 2020-07-14T12:47:31Z
has_accepted_license: '1'
keyword:
- Information estimation
- Time-series
- data analysis
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
page: '135'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '6900'
relation: dissertation_contains
status: public
- id: '281'
relation: dissertation_contains
status: public
- id: '2016'
relation: dissertation_contains
status: public
- id: '1576'
relation: dissertation_contains
status: public
status: public
supervisor:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
title: Estimating information flow in single 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: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2019'
...
---
_id: '9786'
article_processing_charge: No
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Maros
full_name: Pleska, Maros
id: 4569785E-F248-11E8-B48F-1D18A9856A87
last_name: Pleska
orcid: 0000-0001-7460-7479
- 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: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001
apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text
and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001
chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting
Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001.
ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.”
Public Library of Science, 2019.
ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public
Library of Science, 10.1371/journal.pcbi.1007168.s001.
mla: Ruess, Jakob, et al. Supporting Text and Results. Public Library of
Science, 2019, doi:10.1371/journal.pcbi.1007168.s001.
short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019).
date_created: 2021-08-06T08:23:43Z
date_published: 2019-07-02T00:00:00Z
date_updated: 2023-08-29T07:10:05Z
day: '02'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pcbi.1007168.s001
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '6784'
relation: used_in_publication
status: public
status: public
title: Supporting text and results
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2019'
...
---
_id: '281'
abstract:
- lang: eng
text: 'Although cells respond specifically to environments, how environmental identity
is encoded intracellularly is not understood. Here, we study this organization
of information in budding yeast by estimating the mutual information between environmental
transitions and the dynamics of nuclear translocation for 10 transcription factors.
Our method of estimation is general, scalable, and based on decoding from single
cells. The dynamics of the transcription factors are necessary to encode the highest
amounts of extracellular information, and we show that information is transduced
through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can
encode the nature of multiple stresses, but only if stress is high; specialists
(Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly
and for a wider range of magnitudes. In particular, Dot6 encodes almost as much
information as Msn2, the master regulator of the environmental stress response.
Each transcription factor reports differently, and it is only their collective
behavior that distinguishes between multiple environmental states. Changes in
the dynamics of the localization of transcription factors thus constitute a precise,
distributed internal representation of extracellular change. We predict that such
multidimensional representations are common in cellular decision-making.'
acknowledgement: This work was supported by the Biotechnology and Biological Sciences
Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences
Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to
G.T.).
article_processing_charge: No
article_type: original
author:
- first_name: Alejandro
full_name: Granados, Alejandro
last_name: Granados
- first_name: Julian
full_name: Pietsch, Julian
last_name: Pietsch
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Isebail
full_name: Farquhar, Isebail
last_name: Farquhar
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Peter
full_name: Swain, Peter
last_name: Swain
citation:
ama: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed
and dynamic intracellular organization of extracellular information. PNAS.
2018;115(23):6088-6093. doi:10.1073/pnas.1716659115
apa: Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G.,
& Swain, P. (2018). Distributed and dynamic intracellular organization of
extracellular information. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1716659115
chicago: Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar,
Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS. National Academy of Sciences, 2018.
https://doi.org/10.1073/pnas.1716659115.
ieee: A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and
P. Swain, “Distributed and dynamic intracellular organization of extracellular
information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp.
6088–6093, 2018.
ista: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018.
Distributed and dynamic intracellular organization of extracellular information.
PNAS. 115(23), 6088–6093.
mla: Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS, vol. 115, no. 23, National Academy
of Sciences, 2018, pp. 6088–93, doi:10.1073/pnas.1716659115.
short: A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P.
Swain, PNAS 115 (2018) 6088–6093.
date_created: 2018-12-11T11:45:35Z
date_published: 2018-06-05T00:00:00Z
date_updated: 2023-09-11T12:58:24Z
day: '05'
department:
- _id: GaTk
doi: 10.1073/pnas.1716659115
external_id:
isi:
- '000434114900071'
pmid:
- '29784812'
intvolume: ' 115'
isi: 1
issue: '23'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/early/2017/09/21/192039
month: '06'
oa: 1
oa_version: Preprint
page: 6088 - 6093
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7618'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Distributed and dynamic intracellular organization of extracellular information
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '292'
abstract:
- lang: eng
text: 'Retina is a paradigmatic system for studying sensory encoding: the transformation
of light into spiking activity of ganglion cells. The inverse problem, where stimulus
is reconstructed from spikes, has received less attention, especially for complex
stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred
neurons from a dense patch in a rat retina and decoded movies of multiple small
randomly-moving discs. We constructed nonlinear (kernelized and neural network)
decoders that improved significantly over linear results. An important contribution
to this was the ability of nonlinear decoders to reliably separate between neural
responses driven by locally fluctuating light signals, and responses at locally
constant light driven by spontaneous-like activity. This improvement crucially
depended on the precise, non-Poisson temporal structure of individual spike trains,
which originated in the spike-history dependence of neural responses. We propose
a general principle by which downstream circuitry could discriminate between spontaneous
and stimulus-driven activity based solely on higher-order statistical structure
in the incoming spike trains.'
article_number: e1006057
article_processing_charge: Yes
article_type: original
author:
- first_name: Vicent
full_name: Botella Soler, Vicent
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Georg S
full_name: Martius, Georg S
last_name: Martius
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. Nonlinear decoding
of a complex movie from the mammalian retina. PLoS Computational Biology.
2018;14(5). doi:10.1371/journal.pcbi.1006057
apa: Botella Soler, V., Deny, S., Martius, G. S., Marre, O., & Tkačik, G. (2018).
Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1006057
chicago: Botella Soler, Vicente, Stephane Deny, Georg S Martius, Olivier Marre,
and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.”
PLoS Computational Biology. Public Library of Science, 2018. https://doi.org/10.1371/journal.pcbi.1006057.
ieee: V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkačik, “Nonlinear
decoding of a complex movie from the mammalian retina,” PLoS Computational
Biology, vol. 14, no. 5. Public Library of Science, 2018.
ista: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. 2018. Nonlinear decoding
of a complex movie from the mammalian retina. PLoS Computational Biology. 14(5),
e1006057.
mla: Botella Soler, Vicente, et al. “Nonlinear Decoding of a Complex Movie from
the Mammalian Retina.” PLoS Computational Biology, vol. 14, no. 5, e1006057,
Public Library of Science, 2018, doi:10.1371/journal.pcbi.1006057.
short: V. Botella Soler, S. Deny, G.S. Martius, O. Marre, G. Tkačik, PLoS Computational
Biology 14 (2018).
date_created: 2018-12-11T11:45:39Z
date_published: 2018-05-10T00:00:00Z
date_updated: 2024-02-21T13:45:25Z
day: '10'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1006057
ec_funded: 1
external_id:
isi:
- '000434012100002'
file:
- access_level: open_access
checksum: 3026f94d235219e15514505fdbadf34e
content_type: application/pdf
creator: dernst
date_created: 2019-02-13T11:07:15Z
date_updated: 2020-07-14T12:45:53Z
file_id: '5974'
file_name: 2018_Plos_Botella_Soler.pdf
file_size: 3460786
relation: main_file
file_date_updated: 2020-07-14T12:45:53Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
issue: '5'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
project:
- _id: 25CBA828-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '720270'
name: Human Brain Project Specific Grant Agreement 1 (HBP SGA 1)
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/video-of-moving-discs-reconstructed-from-rat-retinal-neuron-signals/
record:
- id: '5584'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Nonlinear decoding of a complex movie from the mammalian retina
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 14
year: '2018'
...
---
_id: '305'
abstract:
- lang: eng
text: The hanging-drop network (HDN) is a technology platform based on a completely
open microfluidic network at the bottom of an inverted, surface-patterned substrate.
The platform is predominantly used for the formation, culturing, and interaction
of self-assembled spherical microtissues (spheroids) under precisely controlled
flow conditions. Here, we describe design, fabrication, and operation of microfluidic
hanging-drop networks.
acknowledgement: This work was financially supported by FP7 of the EU through the
project “Body on a chip,” ICT-FET-296257, and the ERC Advanced Grant “NeuroCMOS”
(contract 267351), as well as by an individual Ambizione Grant 142440 from the Swiss
National Science Foundation for Olivier Frey. The research leading to these results
also 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]. We would like to thank Alexander Stettler, ETH Zurich for his expertise
and support in the cleanroom, and we acknowledge the Single Cell Unit of D-BSSE,
ETH Zurich for assistance in microscopy issues. M.L. is grateful to the members
of the Guet and Tkačik groups, IST Austria, for valuable comments and support.
alternative_title:
- MIMB
author:
- first_name: Patrick
full_name: Misun, Patrick
last_name: Misun
- first_name: Axel
full_name: Birchler, Axel
last_name: Birchler
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Andreas
full_name: Hierlemann, Andreas
last_name: Hierlemann
- first_name: Olivier
full_name: Frey, Olivier
last_name: Frey
citation:
ama: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. Fabrication and operation
of microfluidic hanging drop networks. Methods in Molecular Biology. 2018;1771:183-202.
doi:10.1007/978-1-4939-7792-5_15
apa: Misun, P., Birchler, A., Lang, M., Hierlemann, A., & Frey, O. (2018). Fabrication
and operation of microfluidic hanging drop networks. Methods in Molecular Biology.
Springer. https://doi.org/10.1007/978-1-4939-7792-5_15
chicago: Misun, Patrick, Axel Birchler, Moritz Lang, Andreas Hierlemann, and Olivier
Frey. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” Methods
in Molecular Biology. Springer, 2018. https://doi.org/10.1007/978-1-4939-7792-5_15.
ieee: P. Misun, A. Birchler, M. Lang, A. Hierlemann, and O. Frey, “Fabrication and
operation of microfluidic hanging drop networks,” Methods in Molecular Biology,
vol. 1771. Springer, pp. 183–202, 2018.
ista: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. 2018. Fabrication and operation
of microfluidic hanging drop networks. Methods in Molecular Biology. 1771, 183–202.
mla: Misun, Patrick, et al. “Fabrication and Operation of Microfluidic Hanging Drop
Networks.” Methods in Molecular Biology, vol. 1771, Springer, 2018, pp.
183–202, doi:10.1007/978-1-4939-7792-5_15.
short: P. Misun, A. Birchler, M. Lang, A. Hierlemann, O. Frey, Methods in Molecular
Biology 1771 (2018) 183–202.
date_created: 2018-12-11T11:45:43Z
date_published: 2018-01-01T00:00:00Z
date_updated: 2021-01-12T07:40:42Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1007/978-1-4939-7792-5_15
ec_funded: 1
intvolume: ' 1771'
language:
- iso: eng
month: '01'
oa_version: None
page: 183 - 202
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Methods in Molecular Biology
publication_status: published
publisher: Springer
publist_id: '7574'
quality_controlled: '1'
scopus_import: 1
status: public
title: Fabrication and operation of microfluidic hanging drop networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 1771
year: '2018'
...
---
_id: '306'
abstract:
- lang: eng
text: A cornerstone of statistical inference, the maximum entropy framework is being
increasingly applied to construct descriptive and predictive models of biological
systems, especially complex biological networks, from large experimental data
sets. Both its broad applicability and the success it obtained in different contexts
hinge upon its conceptual simplicity and mathematical soundness. Here we try to
concisely review the basic elements of the maximum entropy principle, starting
from the notion of ‘entropy’, and describe its usefulness for the analysis of
biological systems. As examples, we focus specifically on the problem of reconstructing
gene interaction networks from expression data and on recent work attempting to
expand our system-level understanding of bacterial metabolism. Finally, we highlight
some extensions and potential limitations of the maximum entropy approach, and
point to more recent developments that are likely to play a key role in the upcoming
challenges of extracting structures and information from increasingly rich, high-throughput
biological data.
article_number: e00596
author:
- first_name: Andrea
full_name: De Martino, Andrea
last_name: De Martino
- 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 A, De Martino D. An introduction to the maximum entropy approach
and its application to inference problems in biology. Heliyon. 2018;4(4).
doi:10.1016/j.heliyon.2018.e00596
apa: De Martino, A., & De Martino, D. (2018). An introduction to the maximum
entropy approach and its application to inference problems in biology. Heliyon.
Elsevier. https://doi.org/10.1016/j.heliyon.2018.e00596
chicago: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum
Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon.
Elsevier, 2018. https://doi.org/10.1016/j.heliyon.2018.e00596.
ieee: A. De Martino and D. De Martino, “An introduction to the maximum entropy approach
and its application to inference problems in biology,” Heliyon, vol. 4,
no. 4. Elsevier, 2018.
ista: De Martino A, De Martino D. 2018. An introduction to the maximum entropy approach
and its application to inference problems in biology. Heliyon. 4(4), e00596.
mla: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum
Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon,
vol. 4, no. 4, e00596, Elsevier, 2018, doi:10.1016/j.heliyon.2018.e00596.
short: A. De Martino, D. De Martino, Heliyon 4 (2018).
date_created: 2018-12-11T11:45:44Z
date_published: 2018-04-01T00:00:00Z
date_updated: 2021-01-12T07:40:46Z
day: '01'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1016/j.heliyon.2018.e00596
ec_funded: 1
file:
- access_level: open_access
checksum: 67010cf5e3b3e0637c659371714a715a
content_type: application/pdf
creator: dernst
date_created: 2019-02-06T07:36:24Z
date_updated: 2020-07-14T12:45:59Z
file_id: '5929'
file_name: 2018_Heliyon_DeMartino.pdf
file_size: 994490
relation: main_file
file_date_updated: 2020-07-14T12:45:59Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '4'
language:
- iso: eng
month: '04'
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: Heliyon
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: 1
status: public
title: An introduction to the maximum entropy approach and its application to inference
problems in biology
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2018'
...
---
_id: '31'
abstract:
- lang: eng
text: Correlations in sensory neural networks have both extrinsic and intrinsic
origins. Extrinsic or stimulus correlations arise from shared inputs to the network
and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations
reflect biophysical mechanisms of interactions between neurons, which are expected
to be robust to changes in the stimulus ensemble. Despite the importance of this
distinction for understanding how sensory networks encode information collectively,
no method exists to reliably separate intrinsic interactions from extrinsic correlations
in neural activity data, limiting our ability to build predictive models of the
network response. In this paper we introduce a general strategy to infer population
models of interacting neurons that collectively encode stimulus information. The
key to disentangling intrinsic from extrinsic correlations is to infer the couplings
between neurons separately from the encoding model and to combine the two using
corrections calculated in a mean-field approximation. We demonstrate the effectiveness
of this approach in retinal recordings. The same coupling network is inferred
from responses to radically different stimulus ensembles, showing that these couplings
indeed reflect stimulus-independent interactions between neurons. The inferred
model predicts accurately the collective response of retinal ganglion cell populations
as a function of the stimulus.
acknowledgement: This work was supported by ANR Trajectory, the French State program
Investissements d’Avenir managed by the Agence Nationale de la Recherche (LIFESENSES;
ANR-10-LABX-65), EC Grant No. H2020-785907 from the Human Brain Project, NIH Grant
No. U01NS090501, and an AVIESAN-UNADEV grant to O.M. M.C. was supported by the Agence
Nationale de la Recherche Jeune Chercheur/Jeune Chercheuse grant (ANR-17-CE37-0013).
article_number: '042410'
article_processing_charge: No
article_type: original
author:
- first_name: Ulisse
full_name: Ferrari, Ulisse
last_name: Ferrari
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Matthew J
full_name: Chalk, Matthew J
last_name: Chalk
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
citation:
ama: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. Separating intrinsic
interactions from extrinsic correlations in a network of sensory neurons. Physical
Review E. 2018;98(4). doi:10.1103/PhysRevE.98.042410
apa: Ferrari, U., Deny, S., Chalk, M. J., Tkačik, G., Marre, O., & Mora, T.
(2018). Separating intrinsic interactions from extrinsic correlations in a network
of sensory neurons. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.98.042410
chicago: Ferrari, Ulisse, Stephane Deny, Matthew J Chalk, Gašper Tkačik, Olivier
Marre, and Thierry Mora. “Separating Intrinsic Interactions from Extrinsic Correlations
in a Network of Sensory Neurons.” Physical Review E. American Physical
Society, 2018. https://doi.org/10.1103/PhysRevE.98.042410.
ieee: U. Ferrari, S. Deny, M. J. Chalk, G. Tkačik, O. Marre, and T. Mora, “Separating
intrinsic interactions from extrinsic correlations in a network of sensory neurons,”
Physical Review E, vol. 98, no. 4. American Physical Society, 2018.
ista: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. 2018. Separating intrinsic
interactions from extrinsic correlations in a network of sensory neurons. Physical
Review E. 98(4), 042410.
mla: Ferrari, Ulisse, et al. “Separating Intrinsic Interactions from Extrinsic Correlations
in a Network of Sensory Neurons.” Physical Review E, vol. 98, no. 4, 042410,
American Physical Society, 2018, doi:10.1103/PhysRevE.98.042410.
short: U. Ferrari, S. Deny, M.J. Chalk, G. Tkačik, O. Marre, T. Mora, Physical Review
E 98 (2018).
date_created: 2018-12-11T11:44:15Z
date_published: 2018-10-17T00:00:00Z
date_updated: 2023-09-18T09:18:44Z
day: '17'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.98.042410
ec_funded: 1
external_id:
isi:
- '000447486100004'
intvolume: ' 98'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/10.1101/243816v2.full
month: '10'
oa: 1
oa_version: Preprint
project:
- _id: 26436750-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '785907'
name: Human Brain Project Specific Grant Agreement 2 (HBP SGA 2)
publication: Physical Review E
publication_identifier:
issn:
- '24700045'
publication_status: published
publisher: American Physical Society
publist_id: '8024'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Separating intrinsic interactions from extrinsic correlations in a network
of sensory neurons
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 98
year: '2018'
...
---
_id: '316'
abstract:
- lang: eng
text: 'Self-incompatibility (SI) is a genetically based recognition system that
functions to prevent self-fertilization and mating among related plants. An enduring
puzzle in SI is how the high diversity observed in nature arises and is maintained.
Based on the underlying recognition mechanism, SI can be classified into two main
groups: self- and non-self recognition. Most work has focused on diversification
within self-recognition systems despite expected differences between the two groups
in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic
population genetic model and stochastic simulations to investigate how novel S-haplotypes
evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI
system. For this model the pathways for diversification involve either the maintenance
or breakdown of SI and can vary in the order of mutations of the female (SRNase)
and male (SLF) components. We show analytically that diversification can occur
with high inbreeding depression and self-pollination, but this varies with evolutionary
pathway and level of completeness (which determines the number of potential mating
partners in the population), and in general is more likely for lower haplotype
number. The conditions for diversification are broader in stochastic simulations
of finite population size. However, the number of haplotypes observed under high
inbreeding and moderate to high self-pollination is less than that commonly observed
in nature. Diversification was observed through pathways that maintain SI as well
as through self-compatible intermediates. Yet the lifespan of diversified haplotypes
was sensitive to their level of completeness. By examining diversification in
a non-self recognition SI system, this model extends our understanding of the
evolution and maintenance of haplotype diversity observed in a self recognition
system common in flowering plants.'
article_processing_charge: No
article_type: original
author:
- first_name: Katarina
full_name: Bodova, Katarina
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bodova
orcid: 0000-0002-7214-0171
- first_name: Tadeas
full_name: Priklopil, Tadeas
id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
last_name: Priklopil
- first_name: David
full_name: Field, David
id: 419049E2-F248-11E8-B48F-1D18A9856A87
last_name: Field
orcid: 0000-0002-4014-8478
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Melinda
full_name: Pickup, Melinda
id: 2C78037E-F248-11E8-B48F-1D18A9856A87
last_name: Pickup
orcid: 0000-0001-6118-0541
citation:
ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways
for the generation of new self-incompatibility haplotypes in a non-self recognition
system. Genetics. 2018;209(3):861-883. doi:10.1534/genetics.118.300748
apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018).
Evolutionary pathways for the generation of new self-incompatibility haplotypes
in a non-self recognition system. Genetics. Genetics Society of America.
https://doi.org/10.1534/genetics.118.300748
chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility
Haplotypes in a Non-Self Recognition System.” Genetics. Genetics Society
of America, 2018. https://doi.org/10.1534/genetics.118.300748.
ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary
pathways for the generation of new self-incompatibility haplotypes in a non-self
recognition system,” Genetics, vol. 209, no. 3. Genetics Society of America,
pp. 861–883, 2018.
ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways
for the generation of new self-incompatibility haplotypes in a non-self recognition
system. Genetics. 209(3), 861–883.
mla: Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility
Haplotypes in a Non-Self Recognition System.” Genetics, vol. 209, no. 3,
Genetics Society of America, 2018, pp. 861–83, doi:10.1534/genetics.118.300748.
short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018)
861–883.
date_created: 2018-12-11T11:45:47Z
date_published: 2018-07-01T00:00:00Z
date_updated: 2025-05-28T11:42:44Z
day: '01'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1534/genetics.118.300748
ec_funded: 1
external_id:
isi:
- '000437171700017'
intvolume: ' 209'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/node/80098.abstract
month: '07'
oa: 1
oa_version: Preprint
page: 861-883
project:
- _id: 25B36484-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '329960'
name: Mating system and the evolutionary dynamics of hybrid zones
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Genetics
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/
record:
- id: '9813'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Evolutionary pathways for the generation of new self-incompatibility haplotypes
in a non-self recognition system
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 209
year: '2018'
...
---
_id: '19'
abstract:
- lang: eng
text: Bacteria regulate genes to survive antibiotic stress, but regulation can be
far from perfect. When regulation is not optimal, mutations that change gene expression
can contribute to antibiotic resistance. It is not systematically understood to
what extent natural gene regulation is or is not optimal for distinct antibiotics,
and how changes in expression of specific genes quantitatively affect antibiotic
resistance. Here we discover a simple quantitative relation between fitness, gene
expression, and antibiotic potency, which rationalizes our observation that a
multitude of genes and even innate antibiotic defense mechanisms have expression
that is critically nonoptimal under antibiotic treatment. First, we developed
a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression
and knockout libraries, finding that resistance to a range of 31 antibiotics could
result from changing expression of a large and functionally diverse set of genes,
in a primarily but not exclusively drug-specific manner. Second, by synthetically
controlling the expression of single-drug and multidrug resistance genes, we observed
that their fitness-expression functions changed dramatically under antibiotic
treatment in accordance with a log-sensitivity relation. Thus, because many genes
are nonoptimally expressed under antibiotic treatment, many regulatory mutations
can contribute to resistance by altering expression and by activating latent defenses.
article_processing_charge: No
article_type: original
author:
- first_name: Adam
full_name: Palmer, Adam
last_name: Palmer
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential
for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684.
doi:10.1093/molbev/msy163
apa: Palmer, A., Chait, R. P., & Kishony, R. (2018). Nonoptimal gene expression
creates latent potential for antibiotic resistance. Molecular Biology and Evolution.
Oxford University Press. https://doi.org/10.1093/molbev/msy163
chicago: Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression
Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and
Evolution. Oxford University Press, 2018. https://doi.org/10.1093/molbev/msy163.
ieee: A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates
latent potential for antibiotic resistance,” Molecular Biology and Evolution,
vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018.
ista: Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent
potential for antibiotic resistance. Molecular Biology and Evolution. 35(11),
2669–2684.
mla: Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for
Antibiotic Resistance.” Molecular Biology and Evolution, vol. 35, no. 11,
Oxford University Press, 2018, pp. 2669–84, doi:10.1093/molbev/msy163.
short: A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018)
2669–2684.
date_created: 2018-12-11T11:44:11Z
date_published: 2018-08-28T00:00:00Z
date_updated: 2023-10-17T11:51:06Z
day: '28'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1093/molbev/msy163
external_id:
isi:
- '000452567200006'
pmid:
- '30169679'
intvolume: ' 35'
isi: 1
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pubmed/30169679
month: '08'
oa: 1
oa_version: Submitted Version
page: 2669 - 2684
pmid: 1
publication: Molecular Biology and Evolution
publication_identifier:
issn:
- 0737-4038
publication_status: published
publisher: Oxford University Press
publist_id: '8036'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Nonoptimal gene expression creates latent potential for antibiotic resistance
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2018'
...
---
_id: '67'
abstract:
- lang: eng
text: 'Gene regulatory networks evolve through rewiring of individual components—that
is, through changes in regulatory connections. However, the mechanistic basis
of regulatory rewiring is poorly understood. Using a canonical gene regulatory
system, we quantify the properties of transcription factors that determine the
evolutionary potential for rewiring of regulatory connections: robustness, tunability
and evolvability. In vivo repression measurements of two repressors at mutated
operator sites reveal their contrasting evolutionary potential: while robustness
and evolvability were positively correlated, both were in trade-off with tunability.
Epistatic interactions between adjacent operators alleviated this trade-off. A
thermodynamic model explains how the differences in robustness, tunability and
evolvability arise from biophysical characteristics of repressor–DNA binding.
The model also uncovers that the energy matrix, which describes how mutations
affect repressor–DNA binding, encodes crucial information about the evolutionary
potential of a repressor. The biophysical determinants of evolutionary potential
for regulatory rewiring constitute a mechanistic framework for understanding network
evolution.'
article_processing_charge: No
article_type: original
author:
- first_name: Claudia
full_name: Igler, Claudia
id: 46613666-F248-11E8-B48F-1D18A9856A87
last_name: Igler
- first_name: Mato
full_name: Lagator, Mato
id: 345D25EC-F248-11E8-B48F-1D18A9856A87
last_name: Lagator
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential
of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution.
2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y
apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018).
Evolutionary potential of transcription factors for gene regulatory rewiring.
Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y
chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin
C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.”
Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y.
ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary
potential of transcription factors for gene regulatory rewiring,” Nature Ecology
and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018.
ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential
of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution.
2(10), 1633–1643.
mla: Igler, Claudia, et al. “Evolutionary Potential of Transcription Factors for
Gene Regulatory Rewiring.” Nature Ecology and Evolution, vol. 2, no. 10,
Nature Publishing Group, 2018, pp. 1633–43, doi:10.1038/s41559-018-0651-y.
short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology
and Evolution 2 (2018) 1633–1643.
date_created: 2018-12-11T11:44:27Z
date_published: 2018-09-10T00:00:00Z
date_updated: 2024-03-25T23:30:27Z
day: '10'
ddc:
- '570'
department:
- _id: CaGu
- _id: GaTk
- _id: JoBo
doi: 10.1038/s41559-018-0651-y
ec_funded: 1
external_id:
isi:
- '000447947600021'
file:
- access_level: open_access
checksum: 383a2e2c944a856e2e821ec8e7bf71b6
content_type: application/pdf
creator: dernst
date_created: 2020-05-14T11:28:52Z
date_updated: 2020-07-14T12:47:37Z
file_id: '7830'
file_name: 2018_NatureEcology_Igler.pdf
file_size: 1135973
relation: main_file
file_date_updated: 2020-07-14T12:47:37Z
has_accepted_license: '1'
intvolume: ' 2'
isi: 1
issue: '10'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Submitted Version
page: 1633 - 1643
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2578D616-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '648440'
name: Selective Barriers to Horizontal Gene Transfer
- _id: 251EE76E-B435-11E9-9278-68D0E5697425
grant_number: '24573'
name: Design principles underlying genetic switch architecture (DOC Fellowship)
publication: Nature Ecology and Evolution
publication_status: published
publisher: Nature Publishing Group
publist_id: '7987'
quality_controlled: '1'
related_material:
record:
- id: '5585'
relation: popular_science
status: public
- id: '6371'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Evolutionary potential of transcription factors for gene regulatory rewiring
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2
year: '2018'
...
---
_id: '457'
abstract:
- lang: eng
text: Temperate bacteriophages integrate in bacterial genomes as prophages and represent
an important source of genetic variation for bacterial evolution, frequently transmitting
fitness-augmenting genes such as toxins responsible for virulence of major pathogens.
However, only a fraction of bacteriophage infections are lysogenic and lead to
prophage acquisition, whereas the majority are lytic and kill the infected bacteria.
Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity
to bacteriophages are expected to act as a double-edged sword and increase the
odds of survival at the cost of depriving bacteria of potentially beneficial prophages.
We show that although restriction-modification systems as mechanisms of innate
immunity prevent both lytic and lysogenic infections indiscriminately in individual
bacteria, they increase the number of prophage-acquiring individuals at the population
level. We find that this counterintuitive result is a consequence of phage-host
population dynamics, in which restriction-modification systems delay infection
onset until bacteria reach densities at which the probability of lysogeny increases.
These results underscore the importance of population-level dynamics as a key
factor modulating costs and benefits of immunity to temperate bacteriophages
article_processing_charge: No
author:
- first_name: Maros
full_name: Pleska, Maros
id: 4569785E-F248-11E8-B48F-1D18A9856A87
last_name: Pleska
orcid: 0000-0001-7460-7479
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Dominik
full_name: Refardt, Dominik
last_name: Refardt
- first_name: Bruce
full_name: Levin, Bruce
last_name: Levin
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics
promotes prophage acquisition in bacteria with innate immunity. Nature Ecology
and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z
apa: Pleska, M., Lang, M., Refardt, D., Levin, B., & Guet, C. C. (2018). Phage-host
population dynamics promotes prophage acquisition in bacteria with innate immunity.
Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0424-z
chicago: Pleska, Maros, Moritz Lang, Dominik Refardt, Bruce Levin, and Calin C Guet.
“Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with
Innate Immunity.” Nature Ecology and Evolution. Springer Nature, 2018.
https://doi.org/10.1038/s41559-017-0424-z.
ieee: M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population
dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature
Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018.
ista: Pleska M, Lang M, Refardt D, Levin B, Guet CC. 2018. Phage-host population
dynamics promotes prophage acquisition in bacteria with innate immunity. Nature
Ecology and Evolution. 2(2), 359–366.
mla: Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition
in Bacteria with Innate Immunity.” Nature Ecology and Evolution, vol. 2,
no. 2, Springer Nature, 2018, pp. 359–66, doi:10.1038/s41559-017-0424-z.
short: M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution
2 (2018) 359–366.
date_created: 2018-12-11T11:46:35Z
date_published: 2018-02-01T00:00:00Z
date_updated: 2023-09-15T12:04:57Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41559-017-0424-z
ec_funded: 1
external_id:
isi:
- '000426516400027'
intvolume: ' 2'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa_version: None
page: 359 - 366
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 251BCBEC-B435-11E9-9278-68D0E5697425
grant_number: RGY0079/2011
name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification
Systems (HFSP Young investigators' grant)
- _id: 251D65D8-B435-11E9-9278-68D0E5697425
grant_number: '24210'
name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems
at the Single-Cell Level (DOC Fellowship)
publication: Nature Ecology and Evolution
publication_status: published
publisher: Springer Nature
publist_id: '7364'
quality_controlled: '1'
related_material:
record:
- id: '202'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Phage-host population dynamics promotes prophage acquisition in bacteria with
innate immunity
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2
year: '2018'
...
---
_id: '543'
abstract:
- lang: eng
text: A central goal in theoretical neuroscience is to predict the response properties
of sensory neurons from first principles. To this end, “efficient coding” posits
that sensory neurons encode maximal information about their inputs given internal
constraints. There exist, however, many variants of efficient coding (e.g., redundancy
reduction, different formulations of predictive coding, robust coding, sparse
coding, etc.), differing in their regimes of applicability, in the relevance of
signals to be encoded, and in the choice of constraints. It is unclear how these
types of efficient coding relate or what is expected when different coding objectives
are combined. Here we present a unified framework that encompasses previously
proposed efficient coding models and extends to unique regimes. We show that optimizing
neural responses to encode predictive information can lead them to either correlate
or decorrelate their inputs, depending on the stimulus statistics; in contrast,
at low noise, efficiently encoding the past always predicts decorrelation. Later,
we investigate coding of naturalistic movies and show that qualitatively different
types of visual motion tuning and levels of response sparsity are predicted, depending
on whether the objective is to recover the past or predict the future. Our approach
promises a way to explain the observed diversity of sensory neural responses,
as due to multiple functional goals and constraints fulfilled by different cell
types and/or circuits.
article_processing_charge: No
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Chalk MJ, Marre O, Tkačik G. Toward a unified theory of efficient, predictive,
and sparse coding. PNAS. 2018;115(1):186-191. doi:10.1073/pnas.1711114115
apa: Chalk, M. J., Marre, O., & Tkačik, G. (2018). Toward a unified theory of
efficient, predictive, and sparse coding. PNAS. National Academy of Sciences.
https://doi.org/10.1073/pnas.1711114115
chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Toward a Unified Theory
of Efficient, Predictive, and Sparse Coding.” PNAS. National Academy of
Sciences, 2018. https://doi.org/10.1073/pnas.1711114115.
ieee: M. J. Chalk, O. Marre, and G. Tkačik, “Toward a unified theory of efficient,
predictive, and sparse coding,” PNAS, vol. 115, no. 1. National Academy
of Sciences, pp. 186–191, 2018.
ista: Chalk MJ, Marre O, Tkačik G. 2018. Toward a unified theory of efficient, predictive,
and sparse coding. PNAS. 115(1), 186–191.
mla: Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive,
and Sparse Coding.” PNAS, vol. 115, no. 1, National Academy of Sciences,
2018, pp. 186–91, doi:10.1073/pnas.1711114115.
short: M.J. Chalk, O. Marre, G. Tkačik, PNAS 115 (2018) 186–191.
date_created: 2018-12-11T11:47:04Z
date_published: 2018-01-02T00:00:00Z
date_updated: 2023-09-19T10:16:35Z
day: '02'
department:
- _id: GaTk
doi: 10.1073/pnas.1711114115
external_id:
isi:
- '000419128700049'
intvolume: ' 115'
isi: 1
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/152660 '
month: '01'
oa: 1
oa_version: Submitted Version
page: 186 - 191
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7273'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Toward a unified theory of efficient, predictive, and sparse coding
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '5584'
abstract:
- lang: eng
text: "This package contains data for the publication \"Nonlinear decoding of a
complex movie from the mammalian retina\" by Deny S. et al, PLOS Comput Biol (2018).
\r\n\r\nThe data consists of\r\n(i) 91 spike sorted, isolated rat retinal ganglion
cells that pass stability and quality criteria, recorded on the multi-electrode
array, in response to the presentation of the complex movie with many randomly
moving dark discs. The responses are represented as 648000 x 91 binary matrix,
where the first index indicates the timebin of duration 12.5 ms, and the second
index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike
in the particular time bin.\r\n(ii) README file and a graphical illustration of
the structure of the experiment, specifying how the 648000 timebins are split
into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments
are exact repeats or unique ball trajectories.\r\n(iii) a 648000 x 400 matrix
of luminance traces for each of the 20 x 20 positions (\"sites\") in the movie
frame, with time that is locked to the recorded raster. The luminance traces are
produced as described in the manuscript by filtering the raw disc movie with a
small gaussian spatial kernel. "
article_processing_charge: No
author:
- first_name: Stephane
full_name: Deny, Stephane
last_name: Deny
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Vicente
full_name: Botella-Soler, Vicente
last_name: Botella-Soler
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding
of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98
apa: Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018).
Nonlinear decoding of a complex movie from the mammalian retina. Institute of
Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98
chicago: Deny, Stephane, Olivier Marre, Vicente Botella-Soler, Georg S Martius,
and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.”
Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:98.
ieee: S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkačik, “Nonlinear
decoding of a complex movie from the mammalian retina.” Institute of Science and
Technology Austria, 2018.
ista: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding
of a complex movie from the mammalian retina, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:98.
mla: Deny, Stephane, et al. Nonlinear Decoding of a Complex Movie from the Mammalian
Retina. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:98.
short: S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018).
datarep_id: '98'
date_created: 2018-12-12T12:31:39Z
date_published: 2018-03-29T00:00:00Z
date_updated: 2024-02-21T13:45:26Z
day: '29'
ddc:
- '570'
department:
- _id: ChLa
- _id: GaTk
doi: 10.15479/AT:ISTA:98
file:
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checksum: 6808748837b9afbbbabc2a356ca2b88a
content_type: application/octet-stream
creator: system
date_created: 2018-12-12T13:02:24Z
date_updated: 2020-07-14T12:47:07Z
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creator: system
date_created: 2018-12-12T13:02:25Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5591'
file_name: IST-2018-98-v1+2_ExperimentStructure.pdf
file_size: 702336
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content_type: application/octet-stream
creator: system
date_created: 2018-12-12T13:02:26Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5592'
file_name: IST-2018-98-v1+3_GoodLocations_area2_20x20.mat
file_size: 432
relation: main_file
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content_type: text/plain
creator: system
date_created: 2018-12-12T13:02:26Z
date_updated: 2020-07-14T12:47:07Z
file_id: '5593'
file_name: IST-2018-98-v1+4_README.txt
file_size: 986
relation: main_file
file_date_updated: 2020-07-14T12:47:07Z
has_accepted_license: '1'
keyword:
- retina
- decoding
- regression
- neural networks
- complex stimulus
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 254D1A94-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 25651-N26
name: Sensitivity to higher-order statistics in natural scenes
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '292'
relation: used_in_publication
status: public
status: public
title: Nonlinear decoding of a complex movie from the mammalian retina
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '5585'
abstract:
- lang: eng
text: Mean repression values and standard error of the mean are given for all operator
mutant libraries.
article_processing_charge: No
author:
- first_name: Claudia
full_name: Igler, Claudia
id: 46613666-F248-11E8-B48F-1D18A9856A87
last_name: Igler
- first_name: Mato
full_name: Lagator, Mato
id: 345D25EC-F248-11E8-B48F-1D18A9856A87
last_name: Lagator
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Data for the paper Evolutionary
potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108
apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018).
Data for the paper Evolutionary potential of transcription factors for gene regulatory
rewiring. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:108
chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin
C Guet. “Data for the Paper Evolutionary Potential of Transcription Factors for
Gene Regulatory Rewiring.” Institute of Science and Technology Austria, 2018.
https://doi.org/10.15479/AT:ISTA:108.
ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Data for
the paper Evolutionary potential of transcription factors for gene regulatory
rewiring.” Institute of Science and Technology Austria, 2018.
ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Data for the paper
Evolutionary potential of transcription factors for gene regulatory rewiring,
Institute of Science and Technology Austria, 10.15479/AT:ISTA:108.
mla: Igler, Claudia, et al. Data for the Paper Evolutionary Potential of Transcription
Factors for Gene Regulatory Rewiring. Institute of Science and Technology
Austria, 2018, doi:10.15479/AT:ISTA:108.
short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, (2018).
datarep_id: '108'
date_created: 2018-12-12T12:31:40Z
date_published: 2018-07-20T00:00:00Z
date_updated: 2024-03-25T23:30:27Z
day: '20'
ddc:
- '576'
department:
- _id: CaGu
- _id: GaTk
doi: 10.15479/AT:ISTA:108
ec_funded: 1
file:
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checksum: 1435781526c77413802adee0d4583cce
content_type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
creator: system
date_created: 2018-12-12T13:02:45Z
date_updated: 2020-07-14T12:47:07Z
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file_name: IST-2018-108-v1+1_data_figures.xlsx
file_size: 16507
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file_date_updated: 2020-07-14T12:47:07Z
has_accepted_license: '1'
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2578D616-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '648440'
name: Selective Barriers to Horizontal Gene Transfer
- _id: 251EE76E-B435-11E9-9278-68D0E5697425
grant_number: '24573'
name: Design principles underlying genetic switch architecture (DOC Fellowship)
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '67'
relation: research_paper
status: public
- id: '6371'
relation: research_paper
status: public
status: public
title: Data for the paper Evolutionary potential of transcription factors for gene
regulatory rewiring
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '5587'
abstract:
- lang: eng
text: "Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E.
coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix
enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose
limited minimal medium, \r\nobtained from the soichiometric matrix by standard
linear algebra (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John
ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in
a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter
of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli
catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with
the Lovasz method.\r\n\r\nlovasz.cpp \r\nThis c++ code file receives in input
the polytope of the feasible steady states of a metabolic network, \r\n(matrix
and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding
the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults
to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we
refer to PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp \r\nThis c++
code file receives in input the polytope of the feasible steady states of a metabolic
network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point
inside and \r\nit gives in output a max entropy sampling at fixed average growth
rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov
chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli
network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015)."
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62
apa: De Martino, D., & Tkačik, G. (2018). Supporting materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:62
chicago: De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science
and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62.
ieee: D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology
Austria, 2018.
ista: De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:62.
mla: De Martino, Daniele, and Gašper Tkačik. Supporting Materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria, 2018, doi:10.15479/AT:ISTA:62.
short: D. De Martino, G. Tkačik, (2018).
datarep_id: '111'
date_created: 2018-12-12T12:31:41Z
date_published: 2018-09-21T00:00:00Z
date_updated: 2024-02-21T13:45:39Z
day: '21'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:62
ec_funded: 1
file:
- access_level: open_access
checksum: 97992e3e8cf8544ec985a48971708726
content_type: application/zip
creator: system
date_created: 2018-12-12T13:05:13Z
date_updated: 2020-07-14T12:47:08Z
file_id: '5641'
file_name: IST-2018-111-v1+1_CODES.zip
file_size: 14376
relation: main_file
file_date_updated: 2020-07-14T12:47:08Z
has_accepted_license: '1'
keyword:
- metabolic networks
- e.coli core
- maximum entropy
- monte carlo markov chain sampling
- ellipsoidal rounding
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '161'
relation: research_paper
status: public
status: public
title: Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE
GROWTH"
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '607'
abstract:
- lang: eng
text: We study the Fokker-Planck equation derived in the large system limit of the
Markovian process describing the dynamics of quantitative traits. The Fokker-Planck
equation is posed on a bounded domain and its transport and diffusion coefficients
vanish on the domain's boundary. We first argue that, despite this degeneracy,
the standard no-flux boundary condition is valid. We derive the weak formulation
of the problem and prove the existence and uniqueness of its solutions by constructing
the corresponding contraction semigroup on a suitable function space. Then, we
prove that for the parameter regime with high enough mutation rate the problem
exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next,
we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt)
method for approximation of observables (moments) of the Fokker-Planck solution,
which can be interpreted as a nonlinear Galerkin approximation. The limited applicability
of the DynMaxEnt method inspires us to introduce its modified version that is
valid for the whole range of admissible parameters. Finally, we present several
numerical experiments to demonstrate the performance of both the original and
modified DynMaxEnt methods. We observe that in the parameter regimes where both
methods are valid, the modified one exhibits slightly better approximation properties
compared to the original one.
acknowledgement: "JH and PM are funded by KAUST baseline funds and grant no. 1000000193
.\r\nWe thank Nicholas Barton (IST Austria) for his useful comments and suggestions.
\r\n\r\n"
article_processing_charge: No
arxiv: 1
author:
- first_name: Katarina
full_name: Bodova, Katarina
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bodova
orcid: 0000-0002-7214-0171
- first_name: Jan
full_name: Haskovec, Jan
last_name: Haskovec
- first_name: Peter
full_name: Markowich, Peter
last_name: Markowich
citation:
ama: 'Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation
for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena.
2018;376-377:108-120. doi:10.1016/j.physd.2017.10.015'
apa: 'Bodova, K., Haskovec, J., & Markowich, P. (2018). Well posedness and maximum
entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear
Phenomena. Elsevier. https://doi.org/10.1016/j.physd.2017.10.015'
chicago: 'Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and
Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica
D: Nonlinear Phenomena. Elsevier, 2018. https://doi.org/10.1016/j.physd.2017.10.015.'
ieee: 'K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy
approximation for the dynamics of quantitative traits,” Physica D: Nonlinear
Phenomena, vol. 376–377. Elsevier, pp. 108–120, 2018.'
ista: 'Bodova K, Haskovec J, Markowich P. 2018. Well posedness and maximum entropy
approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena.
376–377, 108–120.'
mla: 'Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation
for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena,
vol. 376–377, Elsevier, 2018, pp. 108–20, doi:10.1016/j.physd.2017.10.015.'
short: 'K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377
(2018) 108–120.'
date_created: 2018-12-11T11:47:28Z
date_published: 2018-08-01T00:00:00Z
date_updated: 2023-09-19T10:38:34Z
day: '01'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1016/j.physd.2017.10.015
external_id:
arxiv:
- '1704.08757'
isi:
- '000437962900012'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1704.08757
month: '08'
oa: 1
oa_version: Submitted Version
page: 108-120
publication: 'Physica D: Nonlinear Phenomena'
publication_status: published
publisher: Elsevier
publist_id: '7198'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Well posedness and maximum entropy approximation for the dynamics of quantitative
traits
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 376-377
year: '2018'
...
---
_id: '161'
abstract:
- lang: eng
text: 'Which properties of metabolic networks can be derived solely from stoichiometry?
Predictive results have been obtained by flux balance analysis (FBA), by postulating
that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization
of FBA to single-cell level using maximum entropy modeling, which we extend and
test experimentally. Specifically, we define for Escherichia coli metabolism a
flux distribution that yields the experimental growth rate: the model, containing
FBA as a limit, provides a better match to measured fluxes and it makes a wide
range of predictions: on flux variability, regulation, and correlations; on the
relative importance of stoichiometry vs. optimization; on scaling relations for
growth rate distributions. We validate the latter here with single-cell data at
different sub-inhibitory antibiotic concentrations. The model quantifies growth
optimization as emerging from the interplay of competitive dynamics in the population
and regulation of metabolism at the level of single cells.'
article_number: '2988'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Andersson Anna
full_name: Mc, Andersson Anna
last_name: Mc
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications.
2018;9(1). doi:10.1038/s41467-018-05417-9
apa: De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018).
Statistical mechanics for metabolic networks during steady state growth. Nature
Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9
chicago: De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet,
and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady
State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9.
ieee: D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical
mechanics for metabolic networks during steady state growth,” Nature Communications,
vol. 9, no. 1. Springer Nature, 2018.
ista: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications. 9(1),
2988.
mla: De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during
Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer
Nature, 2018, doi:10.1038/s41467-018-05417-9.
short: D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications
9 (2018).
date_created: 2018-12-11T11:44:57Z
date_published: 2018-07-30T00:00:00Z
date_updated: 2024-02-21T13:45:39Z
day: '30'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.1038/s41467-018-05417-9
ec_funded: 1
external_id:
isi:
- '000440149300021'
file:
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checksum: 3ba7ab27b27723c7dcf633e8fc1f8f18
content_type: application/pdf
creator: dernst
date_created: 2018-12-17T16:44:28Z
date_updated: 2020-07-14T12:45:06Z
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file_name: 2018_NatureComm_DeMartino.pdf
file_size: 1043205
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has_accepted_license: '1'
intvolume: ' 9'
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issue: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Nature Communications
publication_status: published
publisher: Springer Nature
publist_id: '7760'
quality_controlled: '1'
related_material:
record:
- id: '5587'
relation: popular_science
status: public
scopus_import: '1'
status: public
title: Statistical mechanics for metabolic networks during steady state growth
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 9
year: '2018'
...
---
_id: '9813'
abstract:
- lang: eng
text: 'File S1 contains figures that clarify the following features: (i) effect
of population size on the average number/frequency of SI classes, (ii) changes
in the minimal completeness deficit in time for a single class, and (iii) diversification
diagrams for all studied pathways, including the summary figure for k = 8. File
S2 contains the code required for a stochastic simulation of the SLF system with
an example. This file also includes the output in the form of figures and tables.'
article_processing_charge: No
author:
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Tadeas
full_name: Priklopil, Tadeas
id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
last_name: Priklopil
- first_name: David
full_name: Field, David
id: 419049E2-F248-11E8-B48F-1D18A9856A87
last_name: Field
orcid: 0000-0002-4014-8478
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Melinda
full_name: Pickup, Melinda
id: 2C78037E-F248-11E8-B48F-1D18A9856A87
last_name: Pickup
orcid: 0000-0001-6118-0541
citation:
ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material
for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1
apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018).
Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1
chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society
of America, 2018. https://doi.org/10.25386/genetics.6148304.v1.
ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental
material for Bodova et al., 2018.” Genetics Society of America, 2018.
ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material
for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1.
mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018.
Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1.
short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).
date_created: 2021-08-06T13:04:32Z
date_published: 2018-04-30T00:00:00Z
date_updated: 2025-05-28T11:57:01Z
day: '30'
department:
- _id: NiBa
- _id: GaTk
doi: 10.25386/genetics.6148304.v1
main_file_link:
- open_access: '1'
url: https://doi.org/10.25386/genetics.6148304.v1
month: '04'
oa: 1
oa_version: Published Version
publisher: Genetics Society of America
related_material:
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relation: used_in_publication
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title: Supplemental material for Bodova et al., 2018
type: research_data_reference
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...