---
_id: '15020'
abstract:
- lang: eng
text: "This thesis consists of four distinct pieces of work within theoretical biology,
with two themes in common: the concept of optimization in biological systems,
and the use of information-theoretic tools to quantify biological stochasticity
and statistical uncertainty.\r\nChapter 2 develops a statistical framework for
studying biological systems which we believe to be optimized for a particular
utility function, such as retinal neurons conveying information about visual stimuli.
We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the
expected utility. We explore how such priors aid inference of system parameters
with limited data and enable optimality hypothesis testing: is the utility higher
than by chance?\r\nChapter 3 examines the ultimate biological optimization process:
evolution by natural selection. As some individuals survive and reproduce more
successfully than others, populations evolve towards fitter genotypes and phenotypes.
We formalize this as accumulation of genetic information, and use population genetics
theory to study how much such information can be accumulated per generation and
maintained in the face of random mutation and genetic drift. We identify the population
size and fitness variance as the key quantities that control information accumulation
and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter
3, but from a different perspective: we ask how much genetic information organisms
actually need, in particular in the context of gene regulation. For example, how
much information is needed to bind transcription factors at correct locations
within the genome? Population genetics provides us with a refined answer: with
an increasing population size, populations achieve higher fitness by maintaining
more genetic information. Moreover, regulatory parameters experience selection
pressure to optimize the fitness-information trade-off, i.e. minimize the information
needed for a given fitness. This provides an evolutionary derivation of the optimization
priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information
between a signal and a communication channel output (such as neural activity).
Mutual information is an important utility measure for biological systems, but
its practical use can be difficult due to the large dimensionality of many biological
channels. Sometimes, a lower bound on mutual information is computed by replacing
the high-dimensional channel outputs with decodes (signal estimates). Our result
provides a corresponding upper bound, provided that the decodes are the maximum
posterior estimates of the signal."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
citation:
ama: Hledik M. Genetic information and biological optimization. 2024. doi:10.15479/at:ista:15020
apa: Hledik, M. (2024). Genetic information and biological optimization.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:15020
chicago: Hledik, Michal. “Genetic Information and Biological Optimization.” Institute
of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:15020.
ieee: M. Hledik, “Genetic information and biological optimization,” Institute of
Science and Technology Austria, 2024.
ista: Hledik M. 2024. Genetic information and biological optimization. Institute
of Science and Technology Austria.
mla: Hledik, Michal. Genetic Information and Biological Optimization. Institute
of Science and Technology Austria, 2024, doi:10.15479/at:ista:15020.
short: M. Hledik, Genetic Information and Biological Optimization, Institute of
Science and Technology Austria, 2024.
date_created: 2024-02-23T14:02:04Z
date_published: 2024-02-23T00:00:00Z
date_updated: 2025-06-30T13:21:09Z
day: '23'
ddc:
- '576'
- '519'
department:
- _id: GradSch
- _id: NiBa
- _id: GaTk
doi: 10.15479/at:ista:15020
ec_funded: 1
file:
- access_level: open_access
checksum: b2d3da47c98d481577a4baf68944fe41
content_type: application/pdf
creator: mhledik
date_created: 2024-02-23T13:50:53Z
date_updated: 2024-02-23T13:50:53Z
file_id: '15021'
file_name: hledik thesis pdfa 2b.pdf
file_size: 7102089
relation: main_file
success: 1
- access_level: closed
checksum: eda9b9430da2610fee7ce1c1419a479a
content_type: application/zip
creator: mhledik
date_created: 2024-02-23T13:50:54Z
date_updated: 2024-02-23T14:20:16Z
file_id: '15022'
file_name: hledik thesis source.zip
file_size: 14014790
relation: source_file
file_date_updated: 2024-02-23T14:20:16Z
has_accepted_license: '1'
keyword:
- Theoretical biology
- Optimality
- Evolution
- Information
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: '158'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
grant_number: '101055327'
name: Understanding the evolution of continuous genomes
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7553'
relation: part_of_dissertation
status: public
- id: '7606'
relation: part_of_dissertation
status: public
- id: '12081'
relation: part_of_dissertation
status: public
status: public
supervisor:
- 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: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
title: Genetic information and biological optimization
type: dissertation
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
_id: '14751'
abstract:
- lang: eng
text: 'We consider zero-error communication over a two-transmitter deterministic
adversarial multiple access channel (MAC) governed by an adversary who has access
to the transmissions of both senders (hence called omniscient ) and aims to maliciously
corrupt the communication. None of the encoders, jammer and decoder is allowed
to randomize using private or public randomness. This enforces a combinatorial
nature of the problem. Our model covers a large family of channels studied in
the literature, including all deterministic discrete memoryless noisy or noiseless
MACs. In this work, given an arbitrary two-transmitter deterministic omniscient
adversarial MAC, we characterize when the capacity region: 1) has nonempty interior
(in particular, is two-dimensional); 2) consists of two line segments (in particular,
has empty interior); 3) consists of one line segment (in particular, is one-dimensional);
4) or only contains (0,0) (in particular, is zero-dimensional). This extends a
recent result by Wang et al. (201 9) from the point-to-point setting to the multiple
access setting. Indeed, our converse arguments build upon their generalized Plotkin
bound and involve delicate case analysis. One of the technical challenges is to
take care of both “joint confusability” and “marginal confusability”. In particular,
the treatment of marginal confusability does not follow from the point-to-point
results by Wang et al. Our achievability results follow from random coding with
expurgation.'
acknowledgement: "The author would like to thank Amitalok J. Budkuley and Sidharth
Jaggi for many helpful discussions at the early stage of this work. He would also
like to thank Nir Ailon, Qi Cao, and Chandra Nair for discussions on a related problem
regarding zero-error binary adder MACs.\r\nThe work of Yihan Zhang was supported
by the European Union’s Horizon 2020 Research and Innovation Programme under Grant
682203-ERC-[Inf-Speed-Tradeoff]"
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Yihan
full_name: Zhang, Yihan
id: 2ce5da42-b2ea-11eb-bba5-9f264e9d002c
last_name: Zhang
orcid: 0000-0002-6465-6258
citation:
ama: Zhang Y. Zero-error communication over adversarial MACs. IEEE Transactions
on Information Theory. 2023;69(7):4093-4127. doi:10.1109/tit.2023.3257239
apa: Zhang, Y. (2023). Zero-error communication over adversarial MACs. IEEE Transactions
on Information Theory. Institute of Electrical and Electronics Engineers.
https://doi.org/10.1109/tit.2023.3257239
chicago: Zhang, Yihan. “Zero-Error Communication over Adversarial MACs.” IEEE
Transactions on Information Theory. Institute of Electrical and Electronics
Engineers, 2023. https://doi.org/10.1109/tit.2023.3257239.
ieee: Y. Zhang, “Zero-error communication over adversarial MACs,” IEEE Transactions
on Information Theory, vol. 69, no. 7. Institute of Electrical and Electronics
Engineers, pp. 4093–4127, 2023.
ista: Zhang Y. 2023. Zero-error communication over adversarial MACs. IEEE Transactions
on Information Theory. 69(7), 4093–4127.
mla: Zhang, Yihan. “Zero-Error Communication over Adversarial MACs.” IEEE Transactions
on Information Theory, vol. 69, no. 7, Institute of Electrical and Electronics
Engineers, 2023, pp. 4093–127, doi:10.1109/tit.2023.3257239.
short: Y. Zhang, IEEE Transactions on Information Theory 69 (2023) 4093–4127.
date_created: 2024-01-08T13:04:54Z
date_published: 2023-07-01T00:00:00Z
date_updated: 2024-01-09T08:45:24Z
day: '01'
department:
- _id: MaMo
doi: 10.1109/tit.2023.3257239
external_id:
arxiv:
- '2101.12426'
intvolume: ' 69'
issue: '7'
keyword:
- Computer Science Applications
- Information Systems
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2101.12426
month: '07'
oa: 1
oa_version: Preprint
page: 4093-4127
publication: IEEE Transactions on Information Theory
publication_identifier:
eissn:
- 1557-9654
issn:
- 0018-9448
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Zero-error communication over adversarial MACs
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 69
year: '2023'
...
---
_id: '10602'
abstract:
- lang: eng
text: Transforming ω-automata into parity automata is traditionally done using appearance
records. We present an efficient variant of this idea, tailored to Rabin automata,
and several optimizations applicable to all appearance records. We compare the
methods experimentally and show that our method produces significantly smaller
automata than previous approaches.
acknowledgement: This work is partially funded by the German Research Foundation (DFG)
projects Verified Model Checkers (No. 317422601) and Statistical Unbounded Verification
(No. 383882557), and the Alexander von Humboldt Foundation with funds from the German
Federal Ministry of Education and Research. It is an extended version of [21], including
all proofs together with further explanations and examples. Moreover, we provide
a new, more efficient construction based on (total) preorders, unifying previous
optimizations. Experiments are performed with a new, performant implementation,
comparing our approach to the current state of the art.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Jan
full_name: Kretinsky, Jan
id: 44CEF464-F248-11E8-B48F-1D18A9856A87
last_name: Kretinsky
orcid: 0000-0002-8122-2881
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Clara
full_name: Waldmann, Clara
last_name: Waldmann
- first_name: Maximilian
full_name: Weininger, Maximilian
last_name: Weininger
citation:
ama: Kretinsky J, Meggendorfer T, Waldmann C, Weininger M. Index appearance record
with preorders. Acta Informatica. 2022;59:585-618. doi:10.1007/s00236-021-00412-y
apa: Kretinsky, J., Meggendorfer, T., Waldmann, C., & Weininger, M. (2022).
Index appearance record with preorders. Acta Informatica. Springer Nature.
https://doi.org/10.1007/s00236-021-00412-y
chicago: Kretinsky, Jan, Tobias Meggendorfer, Clara Waldmann, and Maximilian Weininger.
“Index Appearance Record with Preorders.” Acta Informatica. Springer Nature,
2022. https://doi.org/10.1007/s00236-021-00412-y.
ieee: J. Kretinsky, T. Meggendorfer, C. Waldmann, and M. Weininger, “Index appearance
record with preorders,” Acta Informatica, vol. 59. Springer Nature, pp.
585–618, 2022.
ista: Kretinsky J, Meggendorfer T, Waldmann C, Weininger M. 2022. Index appearance
record with preorders. Acta Informatica. 59, 585–618.
mla: Kretinsky, Jan, et al. “Index Appearance Record with Preorders.” Acta Informatica,
vol. 59, Springer Nature, 2022, pp. 585–618, doi:10.1007/s00236-021-00412-y.
short: J. Kretinsky, T. Meggendorfer, C. Waldmann, M. Weininger, Acta Informatica
59 (2022) 585–618.
date_created: 2022-01-06T12:37:27Z
date_published: 2022-10-01T00:00:00Z
date_updated: 2023-08-02T13:49:28Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/s00236-021-00412-y
external_id:
isi:
- '000735765500001'
file:
- access_level: open_access
checksum: bf1c195b6aaf59e8530cf9e3a9d731f7
content_type: application/pdf
creator: cchlebak
date_created: 2022-01-07T07:50:31Z
date_updated: 2022-01-07T07:50:31Z
file_id: '10603'
file_name: 2021_ActaInfor_Křetínský.pdf
file_size: 1066082
relation: main_file
success: 1
file_date_updated: 2022-01-07T07:50:31Z
has_accepted_license: '1'
intvolume: ' 59'
isi: 1
keyword:
- computer networks and communications
- information systems
- software
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 585-618
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Acta Informatica
publication_identifier:
eissn:
- 1432-0525
issn:
- 0001-5903
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Index appearance record with preorders
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: 59
year: '2022'
...
---
_id: '12134'
abstract:
- lang: eng
text: Standard epidemic models exhibit one continuous, second order phase transition
to macroscopic outbreaks. However, interventions to control outbreaks may fundamentally
alter epidemic dynamics. Here we reveal how such interventions modify the type
of phase transition. In particular, we uncover three distinct types of explosive
phase transitions for epidemic dynamics with capacity-limited interventions. Depending
on the capacity limit, interventions may (i) leave the standard second order phase
transition unchanged but exponentially suppress the probability of large outbreaks,
(ii) induce a first-order discontinuous transition to macroscopic outbreaks, or
(iii) cause a secondary explosive yet continuous third-order transition. These
insights highlight inherent limitations in predicting and containing epidemic
outbreaks. More generally our study offers a cornerstone example of a third-order
explosive phase transition in complex systems.
acknowledgement: We acknowledge support from the Volkswagen Foundation under Grant
No. 99720 and the German Federal Ministry for Education and Research (BMBF) under
Grant No. 16ICR01. This research was supported by the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2068—390729961—Cluster
of Excellence Physics of Life of TU Dresden.
article_number: 04LT02
article_processing_charge: No
article_type: original
author:
- first_name: Georg
full_name: Börner, Georg
last_name: Börner
- first_name: Malte
full_name: Schröder, Malte
last_name: Schröder
- first_name: Davide
full_name: Scarselli, Davide
id: 40315C30-F248-11E8-B48F-1D18A9856A87
last_name: Scarselli
orcid: 0000-0001-5227-4271
- first_name: Nazmi B
full_name: Budanur, Nazmi B
id: 3EA1010E-F248-11E8-B48F-1D18A9856A87
last_name: Budanur
orcid: 0000-0003-0423-5010
- first_name: Björn
full_name: Hof, Björn
id: 3A374330-F248-11E8-B48F-1D18A9856A87
last_name: Hof
orcid: 0000-0003-2057-2754
- first_name: Marc
full_name: Timme, Marc
last_name: Timme
citation:
ama: 'Börner G, Schröder M, Scarselli D, Budanur NB, Hof B, Timme M. Explosive transitions
in epidemic dynamics. Journal of Physics: Complexity. 2022;3(4). doi:10.1088/2632-072x/ac99cd'
apa: 'Börner, G., Schröder, M., Scarselli, D., Budanur, N. B., Hof, B., & Timme,
M. (2022). Explosive transitions in epidemic dynamics. Journal of Physics:
Complexity. IOP Publishing. https://doi.org/10.1088/2632-072x/ac99cd'
chicago: 'Börner, Georg, Malte Schröder, Davide Scarselli, Nazmi B Budanur, Björn
Hof, and Marc Timme. “Explosive Transitions in Epidemic Dynamics.” Journal
of Physics: Complexity. IOP Publishing, 2022. https://doi.org/10.1088/2632-072x/ac99cd.'
ieee: 'G. Börner, M. Schröder, D. Scarselli, N. B. Budanur, B. Hof, and M. Timme,
“Explosive transitions in epidemic dynamics,” Journal of Physics: Complexity,
vol. 3, no. 4. IOP Publishing, 2022.'
ista: 'Börner G, Schröder M, Scarselli D, Budanur NB, Hof B, Timme M. 2022. Explosive
transitions in epidemic dynamics. Journal of Physics: Complexity. 3(4), 04LT02.'
mla: 'Börner, Georg, et al. “Explosive Transitions in Epidemic Dynamics.” Journal
of Physics: Complexity, vol. 3, no. 4, 04LT02, IOP Publishing, 2022, doi:10.1088/2632-072x/ac99cd.'
short: 'G. Börner, M. Schröder, D. Scarselli, N.B. Budanur, B. Hof, M. Timme, Journal
of Physics: Complexity 3 (2022).'
date_created: 2023-01-12T12:03:43Z
date_published: 2022-10-25T00:00:00Z
date_updated: 2023-02-13T09:15:13Z
day: '25'
ddc:
- '530'
department:
- _id: BjHo
doi: 10.1088/2632-072x/ac99cd
file:
- access_level: open_access
checksum: 35c5c5cb0eb17ea1b5184755daab9fc9
content_type: application/pdf
creator: dernst
date_created: 2023-01-24T07:24:37Z
date_updated: 2023-01-24T07:24:37Z
file_id: '12350'
file_name: 2022_JourPhysics_Boerner.pdf
file_size: 1006106
relation: main_file
success: 1
file_date_updated: 2023-01-24T07:24:37Z
has_accepted_license: '1'
intvolume: ' 3'
issue: '4'
keyword:
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
publication: 'Journal of Physics: Complexity'
publication_identifier:
issn:
- 2632-072X
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Explosive transitions in epidemic dynamics
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: 3
year: '2022'
...
---
_id: '12261'
abstract:
- lang: eng
text: 'Dose–response relationships are a general concept for quantitatively describing
biological systems across multiple scales, from the molecular to the whole-cell
level. A clinically relevant example is the bacterial growth response to antibiotics,
which is routinely characterized by dose–response curves. The shape of the dose–response
curve varies drastically between antibiotics and plays a key role in treatment,
drug interactions, and resistance evolution. However, the mechanisms shaping the
dose–response curve remain largely unclear. Here, we show in Escherichia coli
that the distinctively shallow dose–response curve of the antibiotic trimethoprim
is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth,
which in turn weakens the effect of this antibiotic. At the molecular level, this
feedback is caused by the upregulation of the drug target dihydrofolate reductase
(FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim
but follows a universal trend line that depends primarily on the growth rate,
irrespective of its cause. Rewiring the feedback loop alters the dose–response
curve in a predictable manner, which we corroborate using a mathematical model
of cellular resource allocation and growth. Our results indicate that growth-mediated
feedback loops may shape drug responses more generally and could be exploited
to design evolutionary traps that enable selection against drug resistance.'
acknowledged_ssus:
- _id: M-Shop
acknowledgement: This work was in part supported by Human Frontier Science Program
GrantRGP0042/2013, Marie Curie Career Integration Grant303507, AustrianScience Fund
(FWF) Grant P27201-B22, and German Research Foundation(DFG) Collaborative Research
Center (SFB)1310to TB. SAA was supportedby the European Union’s Horizon2020Research
and Innovation Programunder the Marie Skłodowska-Curie Grant agreement No707352.
We wouldlike to thank the Bollenbach group for regular fruitful discussions. We
areparticularly thankful for the technical assistance of Booshini Fernando andfor
discussions of the theoretical aspects with Gerrit Ansmann. We areindebted to Bor
Kavˇciˇc for invaluable advice, help with setting up theluciferase-based growth
monitoring system, and for sharing plasmids. Weacknowledge the IST Austria Miba
Machine Shop for their support inbuilding a housing for the stacker of the plate
reader, which enabled thehigh-throughput luciferase-based experiments. We are grateful
to RosalindAllen, Bor Kavˇciˇc and Dor Russ for feedback on the manuscript. Open
Accessfunding enabled and organized by Projekt DEAL.
article_number: e10490
article_processing_charge: No
article_type: original
author:
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Tin Yau
full_name: Pang, Tin Yau
last_name: Pang
- first_name: Guillaume
full_name: Chevereau, Guillaume
last_name: Chevereau
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Martin J
full_name: Lercher, Martin J
last_name: Lercher
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. Growth‐mediated
negative feedback shapes quantitative antibiotic response. Molecular Systems
Biology. 2022;18(9). doi:10.15252/msb.202110490
apa: Angermayr, A., Pang, T. Y., Chevereau, G., Mitosch, K., Lercher, M. J., &
Bollenbach, M. T. (2022). Growth‐mediated negative feedback shapes quantitative
antibiotic response. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.202110490
chicago: Angermayr, Andreas, Tin Yau Pang, Guillaume Chevereau, Karin Mitosch, Martin
J Lercher, and Mark Tobias Bollenbach. “Growth‐mediated Negative Feedback Shapes
Quantitative Antibiotic Response.” Molecular Systems Biology. Embo Press,
2022. https://doi.org/10.15252/msb.202110490.
ieee: A. Angermayr, T. Y. Pang, G. Chevereau, K. Mitosch, M. J. Lercher, and M.
T. Bollenbach, “Growth‐mediated negative feedback shapes quantitative antibiotic
response,” Molecular Systems Biology, vol. 18, no. 9. Embo Press, 2022.
ista: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. 2022.
Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular
Systems Biology. 18(9), e10490.
mla: Angermayr, Andreas, et al. “Growth‐mediated Negative Feedback Shapes Quantitative
Antibiotic Response.” Molecular Systems Biology, vol. 18, no. 9, e10490,
Embo Press, 2022, doi:10.15252/msb.202110490.
short: A. Angermayr, T.Y. Pang, G. Chevereau, K. Mitosch, M.J. Lercher, M.T. Bollenbach,
Molecular Systems Biology 18 (2022).
date_created: 2023-01-16T09:58:34Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2023-08-04T09:51:49Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15252/msb.202110490
external_id:
isi:
- '000856482800001'
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intvolume: ' 18'
isi: 1
issue: '9'
keyword:
- Applied Mathematics
- Computational Theory and Mathematics
- General Agricultural and Biological Sciences
- General Immunology and Microbiology
- General Biochemistry
- Genetics and Molecular Biology
- Information Systems
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: Molecular Systems Biology
publication_identifier:
eissn:
- 1744-4292
publication_status: published
publisher: Embo Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Growth‐mediated negative feedback shapes quantitative antibiotic response
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: 18
year: '2022'
...
---
_id: '10861'
abstract:
- lang: eng
text: We introduce in this paper AMT2.0, a tool for qualitative and quantitative
analysis of hybrid continuous and Boolean signals that combine numerical values
and discrete events. The evaluation of the signals is based on rich temporal specifications
expressed in extended signal temporal logic, which integrates timed regular expressions
within signal temporal logic. The tool features qualitative monitoring (property
satisfaction checking), trace diagnostics for explaining and justifying property
violations and specification-driven measurement of quantitative features of the
signal. We demonstrate the tool functionality on several running examples and
case studies, and evaluate its performance.
article_processing_charge: No
article_type: original
author:
- first_name: Dejan
full_name: Nickovic, Dejan
id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87
last_name: Nickovic
- first_name: Olivier
full_name: Lebeltel, Olivier
last_name: Lebeltel
- first_name: Oded
full_name: Maler, Oded
last_name: Maler
- first_name: Thomas
full_name: Ferrere, Thomas
id: 40960E6E-F248-11E8-B48F-1D18A9856A87
last_name: Ferrere
orcid: 0000-0001-5199-3143
- first_name: Dogan
full_name: Ulus, Dogan
last_name: Ulus
citation:
ama: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. AMT 2.0: Qualitative and
quantitative trace analysis with extended signal temporal logic. International
Journal on Software Tools for Technology Transfer. 2020;22(6):741-758. doi:10.1007/s10009-020-00582-z'
apa: 'Nickovic, D., Lebeltel, O., Maler, O., Ferrere, T., & Ulus, D. (2020).
AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal
logic. International Journal on Software Tools for Technology Transfer.
Springer Nature. https://doi.org/10.1007/s10009-020-00582-z'
chicago: 'Nickovic, Dejan, Olivier Lebeltel, Oded Maler, Thomas Ferrere, and Dogan
Ulus. “AMT 2.0: Qualitative and Quantitative Trace Analysis with Extended Signal
Temporal Logic.” International Journal on Software Tools for Technology Transfer.
Springer Nature, 2020. https://doi.org/10.1007/s10009-020-00582-z.'
ieee: 'D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, and D. Ulus, “AMT 2.0: Qualitative
and quantitative trace analysis with extended signal temporal logic,” International
Journal on Software Tools for Technology Transfer, vol. 22, no. 6. Springer
Nature, pp. 741–758, 2020.'
ista: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. 2020. AMT 2.0: Qualitative
and quantitative trace analysis with extended signal temporal logic. International
Journal on Software Tools for Technology Transfer. 22(6), 741–758.'
mla: 'Nickovic, Dejan, et al. “AMT 2.0: Qualitative and Quantitative Trace Analysis
with Extended Signal Temporal Logic.” International Journal on Software Tools
for Technology Transfer, vol. 22, no. 6, Springer Nature, 2020, pp. 741–58,
doi:10.1007/s10009-020-00582-z.'
short: D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, D. Ulus, International Journal
on Software Tools for Technology Transfer 22 (2020) 741–758.
date_created: 2022-03-18T10:10:53Z
date_published: 2020-08-03T00:00:00Z
date_updated: 2023-09-08T11:52:02Z
day: '03'
department:
- _id: ToHe
doi: 10.1007/s10009-020-00582-z
external_id:
isi:
- '000555398600001'
intvolume: ' 22'
isi: 1
issue: '6'
keyword:
- Information Systems
- Software
language:
- iso: eng
month: '08'
oa_version: None
page: 741-758
publication: International Journal on Software Tools for Technology Transfer
publication_identifier:
eissn:
- 1433-2787
issn:
- 1433-2779
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
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relation: earlier_version
status: public
scopus_import: '1'
status: public
title: 'AMT 2.0: Qualitative and quantitative trace analysis with extended signal
temporal logic'
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 22
year: '2020'
...
---
_id: '7369'
abstract:
- lang: eng
text: Neuronal responses to complex stimuli and tasks can encompass a wide range
of time scales. Understanding these responses requires measures that characterize
how the information on these response patterns are represented across multiple
temporal resolutions. In this paper we propose a metric – which we call multiscale
relevance (MSR) – to capture the dynamical variability of the activity of single
neurons across different time scales. The MSR is a non-parametric, fully featureless
indicator in that it uses only the time stamps of the firing activity without
resorting to any a priori covariate or invoking any specific structure in the
tuning curve for neural activity. When applied to neural data from the mEC and
from the ADn and PoS regions of freely-behaving rodents, we found that neurons
having low MSR tend to have low mutual information and low firing sparsity across
the correlates that are believed to be encoded by the region of the brain where
the recordings were made. In addition, neurons with high MSR contain significant
information on spatial navigation and allow to decode spatial position or head
direction as efficiently as those neurons whose firing activity has high mutual
information with the covariate to be decoded and significantly better than the
set of neurons with high local variations in their interspike intervals. Given
these results, we propose that the MSR can be used as a measure to rank and select
neurons for their information content without the need to appeal to any a priori
covariate.
acknowledgement: This research was supported by the Kavli Foundation and the Centre
of Excellence scheme of the Research Council of Norway (Centre for Neural Computation).
RJC is currently receiving funding from the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 754411.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Ryan J
full_name: Cubero, Ryan J
id: 850B2E12-9CD4-11E9-837F-E719E6697425
last_name: Cubero
orcid: 0000-0003-0002-1867
- first_name: Matteo
full_name: Marsili, Matteo
last_name: Marsili
- first_name: Yasser
full_name: Roudi, Yasser
last_name: Roudi
citation:
ama: Cubero RJ, Marsili M, Roudi Y. Multiscale relevance and informative encoding
in neuronal spike trains. Journal of Computational Neuroscience. 2020;48:85-102.
doi:10.1007/s10827-020-00740-x
apa: Cubero, R. J., Marsili, M., & Roudi, Y. (2020). Multiscale relevance and
informative encoding in neuronal spike trains. Journal of Computational Neuroscience.
Springer Nature. https://doi.org/10.1007/s10827-020-00740-x
chicago: Cubero, Ryan J, Matteo Marsili, and Yasser Roudi. “Multiscale Relevance
and Informative Encoding in Neuronal Spike Trains.” Journal of Computational
Neuroscience. Springer Nature, 2020. https://doi.org/10.1007/s10827-020-00740-x.
ieee: R. J. Cubero, M. Marsili, and Y. Roudi, “Multiscale relevance and informative
encoding in neuronal spike trains,” Journal of Computational Neuroscience,
vol. 48. Springer Nature, pp. 85–102, 2020.
ista: Cubero RJ, Marsili M, Roudi Y. 2020. Multiscale relevance and informative
encoding in neuronal spike trains. Journal of Computational Neuroscience. 48,
85–102.
mla: Cubero, Ryan J., et al. “Multiscale Relevance and Informative Encoding in Neuronal
Spike Trains.” Journal of Computational Neuroscience, vol. 48, Springer
Nature, 2020, pp. 85–102, doi:10.1007/s10827-020-00740-x.
short: R.J. Cubero, M. Marsili, Y. Roudi, Journal of Computational Neuroscience
48 (2020) 85–102.
date_created: 2020-01-28T10:34:00Z
date_published: 2020-02-01T00:00:00Z
date_updated: 2023-08-17T14:35:22Z
day: '01'
ddc:
- '004'
- '519'
- '570'
department:
- _id: SaSi
doi: 10.1007/s10827-020-00740-x
ec_funded: 1
external_id:
isi:
- '000515321800006'
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file_date_updated: 2020-07-14T12:47:56Z
has_accepted_license: '1'
intvolume: ' 48'
isi: 1
keyword:
- Time series analysis
- Multiple time scale analysis
- Spike train data
- Information theory
- Bayesian decoding
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 85-102
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Journal of Computational Neuroscience
publication_identifier:
eissn:
- 1573-6873
issn:
- 0929-5313
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multiscale relevance and informative encoding in neuronal spike trains
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: 48
year: '2020'
...
---
_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
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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'
...