title: ERC analysis: web-based inference of gene function via evolutionary rate covariation.
abstract: The recent explosion of comparative genomics data presents an unprecedented opportunity to construct gene networks via the evolutionary rate covariation (ERC) signature. ERC is used to identify genes that experienced similar evolutionary histories, and thereby draws functional associations between them. The ERC Analysis website allows researchers to exploit genome-wide datasets to infer novel genes in any biological function and to explore deep evolutionary connections between distinct pathways and complexes. The website provides five analytical methods, graphical output, statistical support and access to an increasing number of taxonomic groups.
  
  
  METHODS
  Analyses and data at http://csb.pitt.edu/erc_analysis/
  
  
  BACKGROUND
  nclark@pitt.edu.
authors.affiliation: Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors.forename: Nicholas W
authors.initials: NW
authors.lastname: Wolfe
authors.affiliation: Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors.forename: Nathan L
authors.initials: NL
authors.lastname: Clark
mesh_terms: D000818:Animals; D029721:Drosophila Proteins / Q000145:classification / Q000235:genetics* / Q000378:metabolism; D004331:Drosophila melanogaster / Q000235:genetics; D019143:Evolution, Molecular; D005656:Fungal Proteins / Q000145:classification / Q000235:genetics* / Q000378:metabolism; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D016678:Genome; D023281:Genomics / Q000379:methods*; D020407:Internet; D053858:Metabolic Networks and Pathways; D010802:Phylogeny; D013045:Species Specificity; D015003:Yeasts / Q000235:genetics
chemical_list: D029721:Drosophila Proteins; D005656:Fungal Proteins