---
_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: '11669'
abstract:
- lang: eng
text: We study individual rational, Pareto-optimal, and incentive compatible mechanisms
for auctions with heterogeneous items and budget limits. We consider settings
with multiunit demand and additive valuations. For single-dimensional valuations
we prove a positive result for randomized mechanisms, and a negative result for
deterministic mechanisms. While the positive result allows for private budgets,
the negative result is for public budgets. For multidimensional valuations and
public budgets we prove an impossibility result that applies to deterministic
and randomized mechanisms. Taken together this shows the power of randomization
in certain settings with heterogeneous items, but it also shows its limitations.
article_number: '4'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Paul
full_name: Dütting, Paul
last_name: Dütting
- first_name: Monika H
full_name: Henzinger, Monika H
id: 540c9bbd-f2de-11ec-812d-d04a5be85630
last_name: Henzinger
orcid: 0000-0002-5008-6530
- first_name: Martin
full_name: Starnberger, Martin
last_name: Starnberger
citation:
ama: Dütting P, Henzinger MH, Starnberger M. Auctions for heterogeneous items and
budget limits. ACM Transactions on Economics and Computation. 2015;4(1).
doi:10.1145/2818351
apa: Dütting, P., Henzinger, M. H., & Starnberger, M. (2015). Auctions for heterogeneous
items and budget limits. ACM Transactions on Economics and Computation.
Association for Computing Machinery. https://doi.org/10.1145/2818351
chicago: Dütting, Paul, Monika H Henzinger, and Martin Starnberger. “Auctions for
Heterogeneous Items and Budget Limits.” ACM Transactions on Economics and Computation.
Association for Computing Machinery, 2015. https://doi.org/10.1145/2818351.
ieee: P. Dütting, M. H. Henzinger, and M. Starnberger, “Auctions for heterogeneous
items and budget limits,” ACM Transactions on Economics and Computation,
vol. 4, no. 1. Association for Computing Machinery, 2015.
ista: Dütting P, Henzinger MH, Starnberger M. 2015. Auctions for heterogeneous items
and budget limits. ACM Transactions on Economics and Computation. 4(1), 4.
mla: Dütting, Paul, et al. “Auctions for Heterogeneous Items and Budget Limits.”
ACM Transactions on Economics and Computation, vol. 4, no. 1, 4, Association
for Computing Machinery, 2015, doi:10.1145/2818351.
short: P. Dütting, M.H. Henzinger, M. Starnberger, ACM Transactions on Economics
and Computation 4 (2015).
date_created: 2022-07-27T12:09:15Z
date_published: 2015-12-05T00:00:00Z
date_updated: 2022-09-09T12:08:37Z
day: '05'
doi: 10.1145/2818351
extern: '1'
external_id:
arxiv:
- '1209.6448'
intvolume: ' 4'
issue: '1'
keyword:
- Algorithmic game theory
- auction theory
- Clinching auction
- Pareto optimality
- Budget limits
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1209.6448
month: '12'
oa: 1
oa_version: Preprint
publication: ACM Transactions on Economics and Computation
publication_identifier:
eissn:
- 2167-8383
issn:
- 2167-8375
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Auctions for heterogeneous items and budget limits
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2015'
...