Cross-species analysis of biological networks by Bayesian alignment. Export

@article{citeulike:1009993, 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 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 coexpression networks between humans and mice. 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.}, address = {Institut f\"{u}r Theoretische Physik, Universit\"{a}t zu K\"{o}ln, Z\"{u}lpicherstrasse 77, 50937 Cologne, Germany. berg@thp.uni-koeln.de}, author = {Berg, Johannes and L\"{a}ssig, Michael}, citeulike-article-id = {1009993}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0602294103}, citeulike-linkout-1 = {http://www.pnas.org/content/103/29/10967.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/103/29/10967.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/16835301}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=16835301}, day = {18}, doi = {10.1073/pnas.0602294103}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, keywords = {bayes, co-expression, cross-species, evolution, network}, month = {July}, number = {29}, pages = {10967--10972}, posted-at = {2008-10-09 07:08:30}, priority = {2}, title = {Cross-species analysis of biological networks by Bayesian alignment.}, url = {http://dx.doi.org/10.1073/pnas.0602294103}, volume = {103}, year = {2006} }

TY - JOUR ID - citeulike:1009993 L3 - citeulike-article-id:1009993 N2 - 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 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 coexpression networks between humans and mice. 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. IS - 29 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 0027-8424 AD - Institut für Theoretische Physik, Universität zu Köln, Zülpicherstrasse 77, 50937 Cologne, Germany. berg@thp.uni-koeln.de EP - 10972 TI - Cross-species analysis of biological networks by Bayesian alignment. VL - 103 SP - 10967 KW - bayes KW - co-expression KW - cross-species KW - evolution KW - network AU - Berg, Johannes AU - Lässig, Michael PY - 2006/07/18/ UR - http://dx.doi.org/10.1073/pnas.0602294103 ER -