---
_id: '6900'
abstract:
- lang: eng
text: Across diverse biological systems—ranging from neural networks to intracellular
signaling and genetic regulatory networks—the information about changes in the
environment is frequently encoded in the full temporal dynamics of the network
nodes. A pressing data-analysis challenge has thus been to efficiently estimate
the amount of information that these dynamics convey from experimental data. Here
we develop and evaluate decoding-based estimation methods to lower bound the mutual
information about a finite set of inputs, encoded in single-cell high-dimensional
time series data. For biological reaction networks governed by the chemical Master
equation, we derive model-based information approximations and analytical upper
bounds, against which we benchmark our proposed model-free decoding estimators.
In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based
estimators robustly extract a large fraction of the available information from
high-dimensional trajectories with a realistic number of data samples. We apply
these estimators to previously published data on Erk and Ca2+ signaling in mammalian
cells and to yeast stress-response, and find that substantial amount of information
about environmental state can be encoded by non-trivial response statistics even
in stationary signals. We argue that these single-cell, decoding-based information
estimates, rather than the commonly-used tests for significant differences between
selected population response statistics, provide a proper and unbiased measure
for the performance of biological signaling networks.
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
- first_name: Jakob
full_name: Ruess, Jakob
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying
signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290
apa: Cepeda Humerez, S. A., Ruess, J., & Tkačik, G. (2019). Estimating information
in time-varying signals. PLoS Computational Biology. Public Library of
Science. https://doi.org/10.1371/journal.pcbi.1007290
chicago: Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information
in Time-Varying Signals.” PLoS Computational Biology. Public Library of
Science, 2019. https://doi.org/10.1371/journal.pcbi.1007290.
ieee: S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in
time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public
Library of Science, p. e1007290, 2019.
ista: Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying
signals. PLoS computational biology. 15(9), e1007290.
mla: Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.”
PLoS Computational Biology, vol. 15, no. 9, Public Library of Science,
2019, p. e1007290, doi:10.1371/journal.pcbi.1007290.
short: S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019)
e1007290.
date_created: 2019-09-22T22:00:37Z
date_published: 2019-09-03T00:00:00Z
date_updated: 2023-09-07T12:55:21Z
day: '03'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1007290
external_id:
isi:
- '000489741800021'
pmid:
- '31479447'
file:
- access_level: open_access
checksum: 81bdce1361c9aa8395d6fa635fb6ab47
content_type: application/pdf
creator: kschuh
date_created: 2019-10-01T10:53:45Z
date_updated: 2020-07-14T12:47:44Z
file_id: '6925'
file_name: 2019_PLoS_Cepeda-Humerez.pdf
file_size: 3081855
relation: main_file
file_date_updated: 2020-07-14T12:47:44Z
has_accepted_license: '1'
intvolume: ' 15'
isi: 1
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: e1007290
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: PLoS computational biology
publication_identifier:
eissn:
- '15537358'
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Estimating information in time-varying signals
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 15
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: '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: '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: '1576'
abstract:
- lang: eng
text: 'Gene expression is controlled primarily by interactions between transcription
factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured
well by thermodynamic models of regulation. These models, however, neglect regulatory
crosstalk: the possibility that noncognate TFs could initiate transcription, with
potentially disastrous effects for the cell. Here, we estimate the importance
of crosstalk, suggest that its avoidance strongly constrains equilibrium models
of TF binding, and propose an alternative nonequilibrium scheme that implements
kinetic proofreading to suppress erroneous initiation. This proposal is consistent
with the observed covalent modifications of the transcriptional apparatus and
predicts increased noise in gene expression as a trade-off for improved specificity.
Using information theory, we quantify this trade-off to find when optimal proofreading
architectures are favored over their equilibrium counterparts. Such architectures
exhibit significant super-Poisson noise at low expression in steady state.'
article_number: '248101'
author:
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Cepeda Humerez SA, Rieckh G, Tkačik G. Stochastic proofreading mechanism alleviates
crosstalk in transcriptional regulation. Physical Review Letters. 2015;115(24).
doi:10.1103/PhysRevLett.115.248101
apa: Cepeda Humerez, S. A., Rieckh, G., & Tkačik, G. (2015). Stochastic proofreading
mechanism alleviates crosstalk in transcriptional regulation. Physical Review
Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.115.248101
chicago: Cepeda Humerez, Sarah A, Georg Rieckh, and Gašper Tkačik. “Stochastic Proofreading
Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review
Letters. American Physical Society, 2015. https://doi.org/10.1103/PhysRevLett.115.248101.
ieee: S. A. Cepeda Humerez, G. Rieckh, and G. Tkačik, “Stochastic proofreading mechanism
alleviates crosstalk in transcriptional regulation,” Physical Review Letters,
vol. 115, no. 24. American Physical Society, 2015.
ista: Cepeda Humerez SA, Rieckh G, Tkačik G. 2015. Stochastic proofreading mechanism
alleviates crosstalk in transcriptional regulation. Physical Review Letters. 115(24),
248101.
mla: Cepeda Humerez, Sarah A., et al. “Stochastic Proofreading Mechanism Alleviates
Crosstalk in Transcriptional Regulation.” Physical Review Letters, vol.
115, no. 24, 248101, American Physical Society, 2015, doi:10.1103/PhysRevLett.115.248101.
short: S.A. Cepeda Humerez, G. Rieckh, G. Tkačik, Physical Review Letters 115 (2015).
date_created: 2018-12-11T11:52:49Z
date_published: 2015-12-08T00:00:00Z
date_updated: 2023-09-07T12:55:21Z
day: '08'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.115.248101
ec_funded: 1
intvolume: ' 115'
issue: '24'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1504.05716
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '5595'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: 1
status: public
title: Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 115
year: '2015'
...