CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation.

ABSTRACT: Characterising gene function for the ever-increasing number and diversity of species with annotated genomes relies almost entirely on computational prediction methods. These software are also numerous and diverse, each with different strengths and weaknesses as revealed through community benchmarking efforts. Meta-predictors that assess consensus and conflict from individual algorithms should deliver enhanced functional annotations. To exploit the benefits of meta-approaches, we developed CrowdGO, an open-source consensus-based Gene Ontology (GO) term meta-predictor that employs machine learning models with GO term semantic similarities and information contents. By re-evaluating each gene-term annotation, a consensus dataset is produced with high-scoring confident annotations and low-scori

SUBMITTER: Reijnders MJMF 

PROVIDER: S-EPMC9132264 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature