dorsal/arxiv
View SchemaCross-species analysis of biological networks by Bayesian alignment
| Authors | Johannes Berg, Michael Lässig |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0604026 |
| URL | https://arxiv.org/abs/q-bio/0604026 |
| DOI | 10.1073/pnas.0602294103 |
| Journal | PNAS 103 (29), 10967-10972 (2006) |
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.
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"abstract": "Complex interactions between genes or proteins contribute a substantial part\nto phenotypic evolution. Here we develop an evolutionarily grounded method for\nthe cross-species analysis of interaction networks by {\\em alignment}, which\nmaps bona fide functional relationships between genes in different organisms.\nNetwork alignment is based on a scoring function measuring mutual similarities\nbetween networks taking into account their interaction patterns as well as\nsequence similarities between their nodes. High-scoring alignments and optimal\nalignment parameters are inferred by a systematic Bayesian analysis. We apply\nthis method to analyze the evolution of co-expression networks between human\nand mouse. We find evidence for significant conservation of gene expression\nclusters and give network-based predictions of gene function. We discuss\nexamples where cross-species functional relationships between genes do not\nconcur with sequence similarity.",
"arxiv_id": "q-bio/0604026",
"authors": [
"Johannes Berg",
"Michael L\u00e4ssig"
],
"categories": [
"q-bio.MN",
"cond-mat.dis-nn",
"q-bio.GN"
],
"doi": "10.1073/pnas.0602294103",
"journal_ref": "PNAS 103 (29), 10967-10972 (2006)",
"title": "Cross-species analysis of biological networks by Bayesian alignment",
"url": "https://arxiv.org/abs/q-bio/0604026"
},
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