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Modeling genome evolution with a diffusion approximation of a birth-and-death process
Author(s) -
Georgy P. Karev,
Faina Berezovskaya,
Eugene V. Koonin
Publication year - 2005
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bti1202
Subject(s) - diffusion , stationary distribution , genome evolution , statistical physics , phase portrait , genome , punctuated equilibrium , discrete time and continuous time , computer science , mathematics , physics , biology , evolutionary biology , genetics , statistics , bifurcation , nonlinear system , quantum mechanics , markov chain , gene , thermodynamics
In our previous studies, we developed discrete-space birth, death and innovation models (BDIMs) of genome evolution. These models explain the origin of the characteristic Pareto distribution of paralogous gene family sizes in genomes, and model parameters that provide for the evolution of these distributions within a realistic time frame have been identified. However, extracting the temporal dynamics of genome evolution from discrete-space BDIM was not technically feasible. We were interested in obtaining dynamic portraits of the genome evolution process by developing a diffusion approximation of BDIM.

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