Nicholas W Wolfe1, Nathan L Clark1. 1. Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Abstract
UNLABELLED: 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. AVAILABILITY AND IMPLEMENTATION: Analyses and data at http://csb.pitt.edu/erc_analysis/ CONTACT: nclark@pitt.edu.
UNLABELLED: 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. AVAILABILITY AND IMPLEMENTATION: Analyses and data at http://csb.pitt.edu/erc_analysis/ CONTACT: nclark@pitt.edu.
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