Cross-species analysis of biological networks by Bayesian alignment
Abstract
Complex interactions between genes or proteins contribute a substantial part to phenotypic evolution. Here we develop an evolutionarily grounded method for the cross-species analysis of interaction networks by {\em alignment}, which maps bona fide functional relationships between genes in different organisms. Network alignment is based on a scoring function measuring mutual similarities between networks taking into account their interaction patterns as well as sequence similarities between their nodes. High-scoring alignments and optimal alignment parameters are inferred by a systematic Bayesian analysis. We apply this method to analyze the evolution of co-expression networks between human and mouse. We find evidence for significant conservation of gene expression clusters and give network-based predictions of gene function. We discuss examples where cross-species functional relationships between genes do not concur with sequence similarity.
Keywords
Cite
@article{arxiv.q-bio/0604026,
title = {Cross-species analysis of biological networks by Bayesian alignment},
author = {Johannes Berg and Michael Lässig},
journal= {arXiv preprint arXiv:q-bio/0604026},
year = {2009}
}
Comments
Published version - new title and figure, some changes to the text. 10 pages, 5 figures. Supporting text is available from the authors