ERC analysis: web-based inference of gene function via evolutionary rate covariation.

Area of Science:

• Genomics
• Bioinformatics
• Evolutionary Biology

Background:

• Comparative genomics data is rapidly expanding.
• Evolutionary Rate Covariation (ERC) identifies genes with similar evolutionary histories.
• This approach reveals functional associations between genes.

Purpose of the Study:

• To introduce the ERC Analysis website for constructing gene networks.
• To enable researchers to infer novel genes and explore evolutionary connections.
• To provide a user-friendly platform for analyzing genome-wide datasets.

Main Methods:

• Utilizes the evolutionary rate covariation (ERC) signature.
• Leverages genome-wide datasets for analysis.
• Offers five distinct analytical methods with graphical output and statistical support.

Main Results:

• Enables the construction of gene networks based on evolutionary history.
• Facilitates the identification of genes with shared evolutionary trajectories.
• Provides insights into functional associations and evolutionary connections between biological pathways.

Conclusions:

• The ERC Analysis website is a valuable resource for comparative genomics research.
• It empowers the discovery of novel gene functions and evolutionary relationships.
• The platform supports an expanding range of taxonomic groups for broader applicability.