---
_id: '9381'
abstract:
- lang: eng
text: 'A game of rock-paper-scissors is an interesting example of an interaction
where none of the pure strategies strictly dominates all others, leading to a
cyclic pattern. In this work, we consider an unstable version of rock-paper-scissors
dynamics and allow individuals to make behavioural mistakes during the strategy
execution. We show that such an assumption can break a cyclic relationship leading
to a stable equilibrium emerging with only one strategy surviving. We consider
two cases: completely random mistakes when individuals have no bias towards any
strategy and a general form of mistakes. Then, we determine conditions for a strategy
to dominate all other strategies. However, given that individuals who adopt a
dominating strategy are still prone to behavioural mistakes in the observed behaviour,
we may still observe extinct strategies. That is, behavioural mistakes in strategy
execution stabilise evolutionary dynamics leading to an evolutionary stable and,
potentially, mixed co-existence equilibrium.'
acknowledgement: Authors would like to thank Christian Hilbe and Martin Nowak for
their inspiring and very helpful feedback on the manuscript.
article_number: e1008523
article_processing_charge: No
article_type: original
author:
- first_name: Maria
full_name: Kleshnina, Maria
id: 4E21749C-F248-11E8-B48F-1D18A9856A87
last_name: Kleshnina
- first_name: Sabrina S.
full_name: Streipert, Sabrina S.
last_name: Streipert
- first_name: Jerzy A.
full_name: Filar, Jerzy A.
last_name: Filar
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
citation:
ama: Kleshnina M, Streipert SS, Filar JA, Chatterjee K. Mistakes can stabilise the
dynamics of rock-paper-scissors games. PLoS Computational Biology. 2021;17(4).
doi:10.1371/journal.pcbi.1008523
apa: Kleshnina, M., Streipert, S. S., Filar, J. A., & Chatterjee, K. (2021).
Mistakes can stabilise the dynamics of rock-paper-scissors games. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1008523
chicago: Kleshnina, Maria, Sabrina S. Streipert, Jerzy A. Filar, and Krishnendu
Chatterjee. “Mistakes Can Stabilise the Dynamics of Rock-Paper-Scissors Games.”
PLoS Computational Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008523.
ieee: M. Kleshnina, S. S. Streipert, J. A. Filar, and K. Chatterjee, “Mistakes can
stabilise the dynamics of rock-paper-scissors games,” PLoS Computational Biology,
vol. 17, no. 4. Public Library of Science, 2021.
ista: Kleshnina M, Streipert SS, Filar JA, Chatterjee K. 2021. Mistakes can stabilise
the dynamics of rock-paper-scissors games. PLoS Computational Biology. 17(4),
e1008523.
mla: Kleshnina, Maria, et al. “Mistakes Can Stabilise the Dynamics of Rock-Paper-Scissors
Games.” PLoS Computational Biology, vol. 17, no. 4, e1008523, Public Library
of Science, 2021, doi:10.1371/journal.pcbi.1008523.
short: M. Kleshnina, S.S. Streipert, J.A. Filar, K. Chatterjee, PLoS Computational
Biology 17 (2021).
date_created: 2021-05-09T22:01:38Z
date_published: 2021-04-01T00:00:00Z
date_updated: 2025-07-14T09:10:04Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1008523
ec_funded: 1
external_id:
isi:
- '000639711200001'
file:
- access_level: open_access
checksum: a94ebe0c4116f5047eaa6029e54d2dac
content_type: application/pdf
creator: kschuh
date_created: 2021-05-11T13:50:06Z
date_updated: 2021-05-11T13:50:06Z
file_id: '9385'
file_name: 2021_pcbi_Kleshnina.pdf
file_size: 1323820
relation: main_file
success: 1
file_date_updated: 2021-05-11T13:50:06Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: PLoS Computational Biology
publication_identifier:
eissn:
- '15537358'
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Mistakes can stabilise the dynamics of rock-paper-scissors games
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: 17
year: '2021'
...
---
_id: '9759'
acknowledgement: The authors thank Inez Lam of Johns Hopkins University for valuable
comments on an earlier version of the manuscript. We also thank the facilitators
of the 2019–2020 eLife Community Ambassador program.
article_number: e1009124
article_processing_charge: Yes
article_type: letter_note
author:
- first_name: Michael John
full_name: Bartlett, Michael John
last_name: Bartlett
- first_name: Feyza N
full_name: Arslan, Feyza N
id: 49DA7910-F248-11E8-B48F-1D18A9856A87
last_name: Arslan
orcid: 0000-0001-5809-9566
- first_name: Adriana
full_name: Bankston, Adriana
last_name: Bankston
- first_name: Sarvenaz
full_name: Sarabipour, Sarvenaz
last_name: Sarabipour
citation:
ama: Bartlett MJ, Arslan FN, Bankston A, Sarabipour S. Ten simple rules to improve
academic work- life balance. PLoS Computational Biology. 2021;17(7). doi:10.1371/journal.pcbi.1009124
apa: Bartlett, M. J., Arslan, F. N., Bankston, A., & Sarabipour, S. (2021).
Ten simple rules to improve academic work- life balance. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1009124
chicago: Bartlett, Michael John, Feyza N Arslan, Adriana Bankston, and Sarvenaz
Sarabipour. “Ten Simple Rules to Improve Academic Work- Life Balance.” PLoS
Computational Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1009124.
ieee: M. J. Bartlett, F. N. Arslan, A. Bankston, and S. Sarabipour, “Ten simple
rules to improve academic work- life balance,” PLoS Computational Biology,
vol. 17, no. 7. Public Library of Science, 2021.
ista: Bartlett MJ, Arslan FN, Bankston A, Sarabipour S. 2021. Ten simple rules to
improve academic work- life balance. PLoS Computational Biology. 17(7), e1009124.
mla: Bartlett, Michael John, et al. “Ten Simple Rules to Improve Academic Work-
Life Balance.” PLoS Computational Biology, vol. 17, no. 7, e1009124, Public
Library of Science, 2021, doi:10.1371/journal.pcbi.1009124.
short: M.J. Bartlett, F.N. Arslan, A. Bankston, S. Sarabipour, PLoS Computational
Biology 17 (2021).
date_created: 2021-08-01T22:01:21Z
date_published: 2021-07-15T00:00:00Z
date_updated: 2023-08-10T14:16:46Z
day: '15'
ddc:
- '613'
department:
- _id: CaHe
doi: 10.1371/journal.pcbi.1009124
external_id:
isi:
- '000677713500008'
pmid:
- '34264932'
file:
- access_level: open_access
checksum: e56d91f0eeadb36f143a90e2c1b3ab63
content_type: application/pdf
creator: cchlebak
date_created: 2021-08-05T12:06:49Z
date_updated: 2021-08-05T12:06:49Z
file_id: '9771'
file_name: 2021_PlosCompBio_Bartlett.pdf
file_size: 693633
relation: main_file
file_date_updated: 2021-08-05T12:06:49Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS Computational Biology
publication_identifier:
eissn:
- '15537358'
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
scopus_import: '1'
status: public
title: Ten simple rules to improve academic work- life balance
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: 17
year: '2021'
...
---
_id: '7212'
abstract:
- lang: eng
text: The fixation probability of a single mutant invading a population of residents
is among the most widely-studied quantities in evolutionary dynamics. Amplifiers
of natural selection are population structures that increase the fixation probability
of advantageous mutants, compared to well-mixed populations. Extensive studies
have shown that many amplifiers exist for the Birth-death Moran process, some
of them substantially increasing the fixation probability or even guaranteeing
fixation in the limit of large population size. On the other hand, no amplifiers
are known for the death-Birth Moran process, and computer-assisted exhaustive
searches have failed to discover amplification. In this work we resolve this disparity,
by showing that any amplification under death-Birth updating is necessarily bounded
and transient. Our boundedness result states that even if a population structure
does amplify selection, the resulting fixation probability is close to that of
the well-mixed population. Our transience result states that for any population
structure there exists a threshold r⋆ such that the population structure ceases
to amplify selection if the mutant fitness advantage r is larger than r⋆. Finally,
we also extend the above results to δ-death-Birth updating, which is a combination
of Birth-death and death-Birth updating. On the positive side, we identify population
structures that maintain amplification for a wide range of values r and δ. These
results demonstrate that amplification of natural selection depends on the specific
mechanisms of the evolutionary process.
article_number: e1007494
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Josef
full_name: Tkadlec, Josef
id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
last_name: Tkadlec
orcid: 0000-0002-1097-9684
- first_name: Andreas
full_name: Pavlogiannis, Andreas
id: 49704004-F248-11E8-B48F-1D18A9856A87
last_name: Pavlogiannis
orcid: 0000-0002-8943-0722
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Martin A.
full_name: Nowak, Martin A.
last_name: Nowak
citation:
ama: Tkadlec J, Pavlogiannis A, Chatterjee K, Nowak MA. Limits on amplifiers of
natural selection under death-Birth updating. PLoS computational biology.
2020;16. doi:10.1371/journal.pcbi.1007494
apa: Tkadlec, J., Pavlogiannis, A., Chatterjee, K., & Nowak, M. A. (2020). Limits
on amplifiers of natural selection under death-Birth updating. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007494
chicago: Tkadlec, Josef, Andreas Pavlogiannis, Krishnendu Chatterjee, and Martin
A. Nowak. “Limits on Amplifiers of Natural Selection under Death-Birth Updating.”
PLoS Computational Biology. Public Library of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007494.
ieee: J. Tkadlec, A. Pavlogiannis, K. Chatterjee, and M. A. Nowak, “Limits on amplifiers
of natural selection under death-Birth updating,” PLoS computational biology,
vol. 16. Public Library of Science, 2020.
ista: Tkadlec J, Pavlogiannis A, Chatterjee K, Nowak MA. 2020. Limits on amplifiers
of natural selection under death-Birth updating. PLoS computational biology. 16,
e1007494.
mla: Tkadlec, Josef, et al. “Limits on Amplifiers of Natural Selection under Death-Birth
Updating.” PLoS Computational Biology, vol. 16, e1007494, Public Library
of Science, 2020, doi:10.1371/journal.pcbi.1007494.
short: J. Tkadlec, A. Pavlogiannis, K. Chatterjee, M.A. Nowak, PLoS Computational
Biology 16 (2020).
date_created: 2019-12-23T13:45:11Z
date_published: 2020-01-17T00:00:00Z
date_updated: 2023-10-17T12:29:47Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1007494
ec_funded: 1
external_id:
arxiv:
- '1906.02785'
isi:
- '000510916500025'
file:
- access_level: open_access
checksum: ce32ee2d2f53aed832f78bbd47e882df
content_type: application/pdf
creator: dernst
date_created: 2020-02-03T07:32:42Z
date_updated: 2020-07-14T12:47:53Z
file_id: '7441'
file_name: 2020_PlosCompBio_Tkadlec.pdf
file_size: 1817531
relation: main_file
file_date_updated: 2020-07-14T12:47:53Z
has_accepted_license: '1'
intvolume: ' 16'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
project:
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '279307'
name: 'Quantitative Graph Games: Theory and Applications'
- _id: 2584A770-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 23499-N23
name: Modern Graph Algorithmic Techniques in Formal Verification
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
publication: PLoS computational biology
publication_identifier:
eissn:
- '15537358'
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '7196'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Limits on amplifiers of natural selection under death-Birth updating
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: 16
year: '2020'
...
---
_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'
...