---
_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'
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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:
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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: '14452'
abstract:
- lang: eng
text: The classical infinitesimal model is a simple and robust model for the inheritance
of quantitative traits. In this model, a quantitative trait is expressed as the
sum of a genetic and an environmental component, and the genetic component of
offspring traits within a family follows a normal distribution around the average
of the parents’ trait values, and has a variance that is independent of the parental
traits. In previous work, we showed that when trait values are determined by the
sum of a large number of additive Mendelian factors, each of small effect, one
can justify the infinitesimal model as a limit of Mendelian inheritance. In this
paper, we show that this result extends to include dominance. We define the model
in terms of classical quantities of quantitative genetics, before justifying it
as a limit of Mendelian inheritance as the number, M, of underlying loci tends
to infinity. As in the additive case, the multivariate normal distribution of
trait values across the pedigree can be expressed in terms of variance components
in an ancestral population and probabilities of identity by descent determined
by the pedigree. Now, with just first-order dominance effects, we require two-,
three-, and four-way identities. We also show that, even if we condition on parental
trait values, the “shared” and “residual” components of trait values within each
family will be asymptotically normally distributed as the number of loci tends
to infinity, with an error of order 1/M−−√. We illustrate our results with some
numerical examples.
acknowledgement: NHB was supported in part by ERC Grants 250152 and 101055327. AV
was partly supported by the chaire Modélisation Mathématique et Biodiversité of
Veolia Environment—Ecole Polytechnique—Museum National d’Histoire Naturelle—Fondation
X.
article_number: iyad133
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- 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: Alison M.
full_name: Etheridge, Alison M.
last_name: Etheridge
- first_name: Amandine
full_name: Véber, Amandine
last_name: Véber
citation:
ama: Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics.
2023;225(2). doi:10.1093/genetics/iyad133
apa: Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal
model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133
chicago: Barton, Nicholas H, Alison M. Etheridge, and Amandine Véber. “The Infinitesimal
Model with Dominance.” Genetics. Oxford Academic, 2023. https://doi.org/10.1093/genetics/iyad133.
ieee: N. H. Barton, A. M. Etheridge, and A. Véber, “The infinitesimal model with
dominance,” Genetics, vol. 225, no. 2. Oxford Academic, 2023.
ista: Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance.
Genetics. 225(2), iyad133.
mla: Barton, Nicholas H., et al. “The Infinitesimal Model with Dominance.” Genetics,
vol. 225, no. 2, iyad133, Oxford Academic, 2023, doi:10.1093/genetics/iyad133.
short: N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).
date_created: 2023-10-29T23:01:15Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2025-05-28T11:42:48Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1093/genetics/iyad133
ec_funded: 1
external_id:
arxiv:
- '2211.03515'
file:
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file_size: 1439032
relation: main_file
success: 1
file_date_updated: 2023-10-30T12:57:53Z
has_accepted_license: '1'
intvolume: ' 225'
issue: '2'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
grant_number: '101055327'
name: Understanding the evolution of continuous genomes
publication: Genetics
publication_identifier:
eissn:
- 1943-2631
issn:
- 0016-6731
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
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title: The infinitesimal model with dominance
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type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 225
year: '2023'
...
---
_id: '12159'
abstract:
- lang: eng
text: The term “haplotype block” is commonly used in the developing field of haplotype-based
inference methods. We argue that the term should be defined based on the structure
of the Ancestral Recombination Graph (ARG), which contains complete information
on the ancestry of a sample. We use simulated examples to demonstrate key features
of the relationship between haplotype blocks and ancestral structure, emphasizing
the stochasticity of the processes that generate them. Even the simplest cases
of neutrality or of a “hard” selective sweep produce a rich structure, often missed
by commonly used statistics. We highlight a number of novel methods for inferring
haplotype structure, based on the full ARG, or on a sequence of trees, and illustrate
how they can be used to define haplotype blocks using an empirical data set. While
the advent of new, computationally efficient methods makes it possible to apply
these concepts broadly, they (and additional new methods) could benefit from adding
features to explore haplotype blocks, as we define them. Understanding and applying
the concept of the haplotype block will be essential to fully exploit long and
linked-read sequencing technologies.
acknowledgement: 'We thank the Barton group for useful discussion and feedback during
the writing of this article. Comments from Roger Butlin, Molly Schumer''s Group,
the tskit development team, editors and three reviewers greatly improved the manuscript.
Funding was provided by SCAS (Natural Sciences Programme, Knut and Alice Wallenberg
Foundation), an FWF Wittgenstein grant (PT1001Z211), an FWF standalone grant (grant
P 32166), and an ERC Advanced Grant. YFC was supported by the Max Planck Society
and an ERC Proof of Concept Grant #101069216 (HAPLOTAGGING).'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Daria
full_name: Shipilina, Daria
id: 428A94B0-F248-11E8-B48F-1D18A9856A87
last_name: Shipilina
orcid: 0000-0002-1145-9226
- first_name: Arka
full_name: Pal, Arka
id: 6AAB2240-CA9A-11E9-9C1A-D9D1E5697425
last_name: Pal
orcid: 0000-0002-4530-8469
- first_name: Sean
full_name: Stankowski, Sean
id: 43161670-5719-11EA-8025-FABC3DDC885E
last_name: Stankowski
- first_name: Yingguang Frank
full_name: Chan, Yingguang Frank
last_name: Chan
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Shipilina D, Pal A, Stankowski S, Chan YF, Barton NH. On the origin and structure
of haplotype blocks. Molecular Ecology. 2023;32(6):1441-1457. doi:10.1111/mec.16793
apa: Shipilina, D., Pal, A., Stankowski, S., Chan, Y. F., & Barton, N. H. (2023).
On the origin and structure of haplotype blocks. Molecular Ecology. Wiley.
https://doi.org/10.1111/mec.16793
chicago: Shipilina, Daria, Arka Pal, Sean Stankowski, Yingguang Frank Chan, and
Nicholas H Barton. “On the Origin and Structure of Haplotype Blocks.” Molecular
Ecology. Wiley, 2023. https://doi.org/10.1111/mec.16793.
ieee: D. Shipilina, A. Pal, S. Stankowski, Y. F. Chan, and N. H. Barton, “On the
origin and structure of haplotype blocks,” Molecular Ecology, vol. 32,
no. 6. Wiley, pp. 1441–1457, 2023.
ista: Shipilina D, Pal A, Stankowski S, Chan YF, Barton NH. 2023. On the origin
and structure of haplotype blocks. Molecular Ecology. 32(6), 1441–1457.
mla: Shipilina, Daria, et al. “On the Origin and Structure of Haplotype Blocks.”
Molecular Ecology, vol. 32, no. 6, Wiley, 2023, pp. 1441–57, doi:10.1111/mec.16793.
short: D. Shipilina, A. Pal, S. Stankowski, Y.F. Chan, N.H. Barton, Molecular Ecology
32 (2023) 1441–1457.
date_created: 2023-01-12T12:09:17Z
date_published: 2023-03-01T00:00:00Z
date_updated: 2023-08-16T08:18:47Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1111/mec.16793
external_id:
isi:
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date_created: 2023-08-16T08:15:41Z
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file_date_updated: 2023-08-16T08:15:41Z
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- Ecology
- Evolution
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language:
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oa: 1
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project:
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grant_number: P32166
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- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
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title: On the origin and structure of haplotype blocks
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...
---
_id: '12949'
abstract:
- lang: eng
text: The classical infinitesimal model is a simple and robust model for the inheritance
of quantitative traits. In this model, a quantitative trait is expressed as the
sum of a genetic and a non-genetic (environmental) component and the genetic component
of offspring traits within a family follows a normal distribution around the average
of the parents’ trait values, and has a variance that is independent of the trait
values of the parents. Although the trait distribution across the whole population
can be far from normal, the trait distributions within families are normally distributed
with a variance-covariance matrix that is determined entirely by that in the
ancestral population and the probabilities of identity determined by the pedigree.
Moreover, conditioning on some of the trait values within the pedigree has predictable
effects on the mean and variance within and between families. In previous work,
Barton et al. (2017), we showed that when trait values are determined by the sum
of a large number of Mendelian factors, each of small effect, one can justify
the infinitesimal model as limit of Mendelian inheritance. It was also shown that
under some forms of epistasis, trait values within a family are still normally
distributed.
article_processing_charge: No
author:
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Barton NH. The infinitesimal model with dominance. 2023. doi:10.15479/AT:ISTA:12949
apa: Barton, N. H. (2023). The infinitesimal model with dominance. Institute of
Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:12949
chicago: Barton, Nicholas H. “The Infinitesimal Model with Dominance.” Institute
of Science and Technology Austria, 2023. https://doi.org/10.15479/AT:ISTA:12949.
ieee: N. H. Barton, “The infinitesimal model with dominance.” Institute of Science
and Technology Austria, 2023.
ista: Barton NH. 2023. The infinitesimal model with dominance, Institute of Science
and Technology Austria, 10.15479/AT:ISTA:12949.
mla: Barton, Nicholas H. The Infinitesimal Model with Dominance. Institute
of Science and Technology Austria, 2023, doi:10.15479/AT:ISTA:12949.
short: N.H. Barton, (2023).
contributor:
- contributor_type: researcher
first_name: Amandine
last_name: Veber
- contributor_type: researcher
first_name: Alison
last_name: Etheridge
date_created: 2023-05-13T09:49:09Z
date_published: 2023-05-13T00:00:00Z
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