EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.

ABSTRACT: The known universe of uncharacterized proteins is expanding far faster than our ability to annotate their functions through laboratory study. Computational annotation approaches rely on similarity to previously studied proteins, thereby ignoring unstudied proteins. Coevolutionary approaches hold promise for injecting new information into our knowledge of the protein universe by linking proteins through 'guilt-by-association'. However, existing coevolutionary algorithms have insufficient accuracy and scalability to connect the entire universe of proteins. We present EvoWeaver, a method that weaves together 12 signals of coevolution to quantify the degree of shared evolution between genes. EvoWeaver accurately identifies proteins involved in protein complexes or separate steps of a biochemic

SUBMITTER: Lakshman AH 

PROVIDER: S-EPMC12022180 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature