Gene family evolution: an in-depth theoretical and simulation analysis of non-linear birth-death-innovation models.

ABSTRACT:

Background

The size distribution of gene families in a broad range of genomes is well approximated by a generalized Pareto function. Evolution of ensembles of gene families can be described with Birth, Death, and Innovation Models (BDIMs). Analysis of the properties of different versions of BDIMs has the potential of revealing important features of genome evolution.

Results

In this work, we extend our previous analysis of stochastic BDIMs. In addition to the previously examined rational BDIMs, we introduce potentially more realistic logistic BDIMs, in which birth/death rates are limited for the largest families, and show that their properties are similar to those of models that include no such limitation. We show that the mean time required for the formation of the largest g

SUBMITTER: Karev GP 

PROVIDER: S-EPMC523855 | biostudies-literature | 2004 Sep

REPOSITORIES: biostudies-literature