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Genomic foundation models trained on DNA sequences have demonstrated remarkable capabilities across diverse biological tasks, from variant effect prediction to genome design. These models are typically trained on massive, publicly sourced…

Genomics · Quantitative Biology 2026-03-31 Charalampos Koilakos , Ioannis Mouratidis , Ilias Georgakopoulos-Soares

Sex in higher diploids carries a two-fold cost of males that should reduce its fitness relative to cloning and result in its extinction. Instead, sex is widespread and it is clonal species that face early obsolescence. One possible reason…

Populations and Evolution · Quantitative Biology 2013-04-24 David Green , Chris Mason

Neural networks and evolutionary computation have a rich intertwined history. They most commonly appear together when an evolutionary algorithm optimises the parameters and topology of a neural network for reinforcement learning problems,…

Neural and Evolutionary Computing · Computer Science 2016-04-15 Alexander W. Churchill , Siddharth Sigtia , Chrisantha Fernando

Any process in which competing solutions replicate with errors and numbers of their copies depend on their respective fitnesses is the evolutionary optimization process. As during carcinogenesis mutated genomes replicate according to their…

Populations and Evolution · Quantitative Biology 2009-12-15 B. Brutovsky , D. Horvath

Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g.…

Populations and Evolution · Quantitative Biology 2024-03-28 Karl Grieshop , Eddie K. H. Ho , Katja R. Kasimatis

Generative Adversarial Networks (GANs) are a class of generative algorithms that have been shown to produce state-of-the art samples, especially in the domain of image creation. The fundamental principle of GANs is to approximate the…

Machine Learning · Statistics 2018-03-22 G. Biau , B. Cadre , M. Sangnier , U. Tanielian

Gene conversion is a mechanism by which a double-strand break in a DNA molecule is repaired using a homologous DNA molecule as a template. As a result, one gene is 'copied and pasted' onto the other gene. It was recently reported that the…

Populations and Evolution · Quantitative Biology 2013-04-08 Shuhei Mano

We have used the Monte Carlo based computer models to show that selection pressure could affect the distribution of recombination hotspots along the chromosome. Close to critical crossover rate, where genomes may switch between the…

Genomics · Quantitative Biology 2015-05-13 Jakub Kowalski , Wojciech Waga , Marta Zawierta , Stanislaw Cebrat

A central biological question is how natural organisms are so evolvable (capable of quickly adapting to new environments). A key driver of evolvability is the widespread modularity of biological networks--their organization as functional,…

Populations and Evolution · Quantitative Biology 2015-03-13 Jeff Clune , Jean-Baptiste Mouret , Hod Lipson

Several recent experiments suggest that sharply bent DNA has a surprisingly high bending flexibility, but the cause of this flexibility is poorly understood. Although excitation of flexible defects can explain these results, whether such…

Biological Physics · Physics 2015-12-22 Peiwen Cong , Liang Dai , Hu Chen , Johan R. C. van der Maarel , Patrick S. Doyle , Jie Yan

Conventional population genetics considers the evolution of a limited number of genotypes corresponding to phenotypes with different fitness. As model phenotypes, in particular RNA secondary structure, have become computationally tractable,…

Populations and Evolution · Quantitative Biology 2008-04-22 Gergely J. Szollosi , Imre Derenyi

Deep Learning (DL) is a surprisingly successful branch of machine learning. The success of DL is usually explained by focusing analysis on a particular recent algorithm and its traits. Instead, we propose that an explanation of the success…

Machine Learning · Computer Science 2022-05-23 Artem Kaznatcheev , Konrad Paul Kording

Genetic programming is the practice of evolving formulas using crossover and mutation of genes representing functional operations. Motivated by genetic evolution we develop and solve two combinatorial games, and we demonstrate some…

Combinatorics · Mathematics 2021-02-02 Melissa A. Huggan , Craig Tennenhouse

Evolution and learning are two of the fundamental mechanisms by which life adapts in order to survive and to transcend limitations. These biological phenomena inspired successful computational methods such as evolutionary algorithms and…

Neural and Evolutionary Computing · Computer Science 2019-05-10 Jan Schuchardt , Vladimir Golkov , Daniel Cremers

The Darwinian paradigm of biological evolution is based on the separability of the variation and selection processes. As a result, the population thinking had always been an integral part of the Darwinian approach. I propose an alternative…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Vasily Ogryzko

A key goal in studies of ecology and evolution is understanding the causes of phenotypic diversity in nature. Most traits of interest, such as those relating to morphology, life-history, immunity and behaviour are quantitative, and…

Populations and Evolution · Quantitative Biology 2022-11-22 Susan E. Johnston , Nancy Chen , Emily B. Josephs

In the evolution of a genome, the gene sequence is sometimes rearranged, for example by transposition of two adjacent gene blocks. In biocombinatorics, one tries to reconstruct these rearrangement incidents from the resulting permutation.…

Combinatorics · Mathematics 2007-05-23 Henrik Eriksson , Kimmo Eriksson , Jonas Sjostrand

It has been known for many years that small fractions of persister cells resist killing in many bacterial colony-antimicrobial confrontations. These persisters are not believed to be mutants. Rather it has been hypothesized that they are…

Cell Behavior · Quantitative Biology 2007-05-23 I. Klapper , P. Gilbert , B. P. Ayati , J. Dockery , P. S. Stewart

Evolutionary multitasking has recently emerged as a novel paradigm that enables the similarities and/or latent complementarities (if present) between distinct optimization tasks to be exploited in an autonomous manner simply by solving them…

Neural and Evolutionary Computing · Computer Science 2016-07-20 Abhishek Gupta , Yew-Soon Ong

Evolution of the reduced density matrix for a subsystem is studied to determine deviations from its Markov character for a system consisting of a closed chain of $N$ oscillators with one of them serving as a subsystem. The dependence on $N$…

Quantum Physics · Physics 2021-02-04 M. A. Braun
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