Biology – Quantitative Biology – Molecular Networks
Scientific paper
2006-04-20
PNAS 103 (29), 10967-10972 (2006)
Biology
Quantitative Biology
Molecular Networks
Published version - new title and figure, some changes to the text. 10 pages, 5 figures. Supporting text is available from the
Scientific paper
10.1073/pnas.0602294103
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.
Berg Johannes
Lässig Michael
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