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相关论文: Optimal Mutation Rates in Dynamic Environments

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This short paper presents an abstract, tunable model of genomic structural change within the cell lifecycle and explores its use with simulated evolution. A well-known Boolean model of genetic regulatory networks is extended to include…

计算工程、金融与科学 · 计算机科学 2012-01-18 Larry Bull

Continuous adaptation to variable environments is crucial for the survival of living organisms. Here, we analyze how adaptation, forecasting, and resource mobilization towards a target state, termed actionability, interact to determine…

细胞行为 · 定量生物学 2024-04-15 Jose M. G. Vilar , Leonor Saiz

When mutation rates are low, natural selection remains effective, and increasing the mutation rate can give rise to an increase in adaptation rate. When mutation rates are high to begin with, however, increasing the mutation rate may have a…

种群与进化 · 定量生物学 2012-11-06 Philip Gerrish , Alexandre Colato , Paul Sniegowski

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization…

分子网络 · 定量生物学 2014-10-24 Steffen Waldherr , Diego A. Oyarzún , Alexander Bockmayr

Living species, ranging from bacteria to animals, exist in environmental conditions that exhibit spatial and temporal heterogeneity which requires them to adapt. Risk-spreading through spontaneous phenotypic variations is a known concept in…

Mutation has traditionally been regarded as an important operator in evolutionary algorithms. In particular, there have been many experimental studies which showed the effectiveness of adapting mutation rates for various static optimization…

人工智能 · 计算机科学 2011-06-06 Tianshi Chen , Yunji Chen , Ke Tang , Guoliang Chen , Xin Yao

A simplified form of the time dependent evolutionary dynamics of a quasispecies model with a rugged fitness landscape is solved via a mapping onto a random flux model whose asymptotic behavior can be described in terms of a random walk. The…

统计力学 · 物理学 2009-11-11 Clement Sire , Satya N. Majumdar , David S. Dean

We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic…

种群与进化 · 定量生物学 2009-11-13 Kavita Jain

In a constantly changing world, animals must account for environmental volatility when making decisions. To appropriately discount older, irrelevant information, they need to learn the rate at which the environment changes. We develop an…

神经元与认知 · 定量生物学 2017-01-12 Adrian E Radillo , Alan Veliz-Cuba , Kresimir Josic , Zachary P Kilpatrick

We present a new method for proving lower bounds on the expected running time of evolutionary algorithms. It is based on fitness-level partitions and an additional condition on transition probabilities between fitness levels. The method is…

神经与进化计算 · 计算机科学 2015-03-19 Dirk Sudholt

We study the distribution of the maximum of a set of random fitnesses with fixed number of mutations in a model of biological evolution. The fitness variables are not independent and the correlations can be varied via a parameter…

统计力学 · 物理学 2015-05-14 Kavita Jain , Abhishek Dasgupta , Gayatri Das

Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depend on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness…

种群与进化 · 定量生物学 2016-08-05 Sona John , Sarada Seetharaman

The rate of the trace distance is used to evaluate quantum speed-up for arbitrary mixed states. Compared with some present methods, the approach based on trace distance can provide an optimal bound to the speed of the evolution. The…

量子物理 · 物理学 2016-11-04 Xiang Hao , Wenjiong Wu

We study biological evolution on a random fitness landscape where correlations are introduced through a linear fitness gradient of strength $c$. When selection is strong and mutations rare the dynamics is a directed uphill walk that…

种群与进化 · 定量生物学 2015-04-16 Su-Chan Park , Ivan G. Szendro , Johannes Neidhart , Joachim Krug

Molecular phenotypes are important links between genomic information and organismic functions, fitness, and evolution. Complex phenotypes, which are also called quantitative traits, often depend on multiple genomic loci. Their evolution…

种群与进化 · 定量生物学 2015-06-12 Armita Nourmohammad , Stephan Schiffels , Michael Laessig

Biological evolution of a population is governed by the fitness landscape, which is a map from genotype to fitness. However, a fitness landscape depends on the organisms environment, and evolution in changing environments is still poorly…

种群与进化 · 定量生物学 2022-09-26 Suman G Das , Joachim Krug , Muhittin Mungan

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist…

种群与进化 · 定量生物学 2017-09-27 Andreas Mayer , Thierry Mora , Olivier Rivoire , Aleksandra M. Walczak

Previous evolutionary studies demonstrated how evaluating evolving agents in variable environmental conditions enable them to develop solutions that are robust to environmental variation. We demonstrate how the robustness of the agents can…

神经与进化计算 · 计算机科学 2018-03-05 Nicola Milano , Jônata Tyska Carvalho , Stefano Nolfi

We present a model of the evolution of control systems in a genome under environmental constraints. The model conceptually follows the Jacob and Monod model of gene control. Genes contain control elements which respond to the internal state…

基因组学 · 定量生物学 2021-06-09 William Bains , Enrico Borriello , Dirk Schulze-Makuch

A simple model of species origin resulted from dynamic features of a population, solely, is developed. The model is based on the evolution optimality in space distribution, and the selection is gone over the mobility. Some biological issues…

种群与进化 · 定量生物学 2008-04-25 Michael G. Sadovsky