EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles

Files

gku442.pdf (637.9 KB)
Downloads: 182

TR Number

Date

2014-07-01

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes.

Description

Keywords

r package, protein, genome, models, mouse

Citation