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Related papers: Dynamics of genetic code evolution: The emergence …

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A heuristic diagram of the evolution of the standard genetic code is presented. It incorporates, in a way that resembles the energy levels of an atom, the physical notion of broken symmetry and it is consistent with original ideas by Crick…

Other Quantitative Biology · Quantitative Biology 2015-12-31 C. Manuel Carlevaro , Ramiro M. Irastorza , Fernando Vericat

Genomic evolution can be viewed as string-editing processes driven by mutations. An understanding of the statistical properties resulting from these mutation processes is of value in a variety of tasks related to biological sequence data,…

Information Theory · Computer Science 2018-12-07 Hao Lou , Farzad Farnoud , Moshe Schwartz , Jehoshua Bruck

Martincorena et al. estimated synonymous diversity ({\theta}s = 2N{\mu}) across 2,930 orthologous gene alignments from 34 Escherichia coli genomes, and found substantial variation among genes in the density of synonymous polymorphisms. They…

Populations and Evolution · Quantitative Biology 2012-10-02 Rohan Maddamsetti , Philip J. Hatcher , Stéphane Cruveiller , Claudine Médigue , Jeffrey E. Barrick , Richard E. Lenski

In a short article submitted to ArXiv [1], Maddamsetti et al. argue that the variation in the neutral mutation rate among genes in Escherichia coli that we recently reported [2] might be explained by horizontal gene transfer (HGT). To…

Populations and Evolution · Quantitative Biology 2012-11-08 Inigo Martincorena , Nicholas M. Luscombe

Genetic algorithms have been used in recent decades to solve a broad variety of search problems. These algorithms simulate natural selection to explore a parameter space in search of solutions for a broad variety of problems. In this paper,…

Neural and Evolutionary Computing · Computer Science 2022-03-25 Yoshio Martinez , Katya Rodriguez , Carlos Gershenson

Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented…

Neural and Evolutionary Computing · Computer Science 2017-12-19 Andres Felipe Cruz Salinas , Jonatan Gomez Perdomo

The modeling of time series is becoming increasingly critical in a wide variety of applications. Overall, data evolves by following different patterns, which are generally caused by different user behaviors. Given a time series, we define…

Machine Learning · Computer Science 2022-07-13 Wenjie Hu , Jianping Huang , Liang Wu , Yang Yang , Zongtao Liu , Zhanlin Sun , Bingshen Yao , Ke Chen

Natural selection explains how life has evolved over millions of years from more primitive forms. The speed at which this happens, however, has sometimes defied formal explanations when based on random (uniformly distributed) mutations.…

Neural and Evolutionary Computing · Computer Science 2018-06-22 Santiago Hernández-Orozco , Narsis A. Kiani , Hector Zenil

In this work, the dynamics of fluctuations in gene expression time series is investigated. By using collected data of gene expression from yeast and human organisms, we found that the fluctuations of gene expression level and its average…

Biomolecules · Quantitative Biology 2007-05-23 J. C. Nacher , T. Ochiai , T. Akutsu

Significant fraction (98.5% in humans) of most animal genomes is non- coding dark matter. Its largely unknown function (1-5) is related to programming (rather than to spontaneous mutations) of accurate adaptation to rapidly changing…

Genomics · Quantitative Biology 2007-08-02 Mark Ya. Azbel

A quantitative theory on the construction and the evolution of the genetic code is proposed. Through introducing the concept of mutational deterioration (MD) and developing a theoretical formalism on MD minimization we have proved: 1, the…

Other Quantitative Biology · Quantitative Biology 2009-08-24 Liaofu Luo

Evolution is the theory that plants and animals today have come from kinds that have existed in the past. Scientists such as Charles Darwin and Alfred Wallace dedicate their life to observe how species interact with their environment, grow,…

Neural and Evolutionary Computing · Computer Science 2022-09-16 Manasa Josyula

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the…

Statistical Mechanics · Physics 2009-10-31 Stefan Bornholdt

Large scale databases are available that contain homologous gene families constructed from hundreds of complete genome sequences from across the three domains of Life. Here we discuss approches of increasing complexity aimed at extracting…

Genomics · Quantitative Biology 2011-02-14 Gergely J Szöllősi , Vincent Daubin

We study the evolution of artificial learning systems by means of selection. Genetic programming is used to generate a sequence of populations of algorithms which can be used by neural networks for supervised learning of a rule that…

Biological Physics · Physics 2009-11-07 Juan Pablo Neirotti , Nestor Caticha

A central goal of evolutionary biology is to explain the origins and distribution of diversity across life. Beyond species or genetic diversity, we also observe diversity in the circuits (genetic or otherwise) underlying complex functional…

Populations and Evolution · Quantitative Biology 2018-06-06 Ali Tehrani-Saleh , Thomas LaBar , Christoph Adami

We propose a physical model to describe the mechanisms of two major scenarios of the genetic code evolution, the codon capture and ambiguous intermediate scenarios, in a consistent manner. We sketch the lowest dimensional version of our…

Populations and Evolution · Quantitative Biology 2009-09-30 Tatsuro Yamashita , Osamu Narikiyo

Genetic sequences are known to possess non-trivial composition together with symmetries in the frequencies of their components. Recently, it has been shown that symmetry and structure are hierarchically intertwined in DNA, suggesting a…

Genomics · Quantitative Biology 2020-09-28 Giampaolo Cristadoro , Mirko Degli Esposti , Eduardo G. Altmann

Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled by evolutionary algorithms that use a representation which…

Neural and Evolutionary Computing · Computer Science 2013-01-18 Benjamin Doerr , Anton Eremeev , Frank Neumann , Madeleine Theile , Christian Thyssen

The idea that there are any large-scale trends in the evolution of biological organisms is highly controversial. It is commonly believed, for example, that there is a large-scale trend in evolution towards increasing complexity, but…

Neural and Evolutionary Computing · Computer Science 2021-06-08 Peter D. Turney