EvoCor

EvoCor predicts genes that are functionally related by integrating evolutionary sequence divergence profiles and tissue-wide gene expression correlations to identify co-evolved and co-expressed gene pairs.

Key Features:

• Integration of Phylogenetic Analysis: EvoCor employs a Hidden Markov Model (HMM) to analyze sequence divergence profiles across multiple genomes to detect evolutionary relationships among genes.
• Gene Expression Correlation: EvoCor incorporates tissue-wide gene expression data to identify correlated expression patterns that support inference of functional linkages, co-regulation, or shared cellular roles.

Scientific Applications:

• Functional Genomics: Predicts genes functionally related to a query gene to generate hypotheses about gene function.
• Systems Biology: Identifies groups of co-evolved and co-expressed genes for network and pathway analysis.
• Personalized Medicine: Supports hypothesis generation about genes and pathways that may be relevant to disease mechanisms.
• Gene Network and Pathway Inference: Facilitates discovery of candidate gene networks and pathways through combined evolutionary and expression evidence.

Methodology:

Integration of phylogenetic data derived from sequence divergence profiles using a Hidden Markov Model with tissue-wide gene expression correlation analyses to predict pairs of genes likely to be functionally linked.