CombFunc

CombFunc predicts protein functions using Gene Ontology (GO) annotations by integrating sequence data, gene expression profiles, protein–protein interaction networks and ConFunc-derived sequence predictions.

Key Features:

• Integration of Multiple Data Sources: CombFunc integrates protein sequence data, gene expression profiles, and protein–protein interaction networks to inform function prediction.
• Combination with ConFunc Methodology: CombFunc incorporates ConFunc sequence-based predictions as part of its functional inference framework.
• Gene Ontology (GO) Annotations: CombFunc assigns GO molecular function and GO biological process terms to proteins.
• Benchmarking Performance: On a benchmark dataset of 1686 proteins, CombFunc achieved precision 0.71 and recall 0.64 for GO molecular function terms, and precision 0.74 and recall 0.41 for GO biological process terms.

Scientific Applications:

• Genomics: Annotating uncharacterized proteins in genomic datasets.
• Proteomics: Assigning GO-based molecular function and biological process annotations in proteomic studies.
• Systems Biology: Integrating predicted functions into network and systems-level analyses.

Methodology:

CombFunc integrates sequence-based predictions (including ConFunc) with gene expression data and protein–protein interaction networks to produce GO-based annotations.