A novel semantic similarity score for protein data analysis

Aim: A similarity evaluation measure for Gene Ontology GO terms is developed. Results: The proposed method takes into account the semantics hidden in ontologies or the term level information content, membership of term, and topology-based similarity measures. The proposed method is evaluated on positive and negative dataset of UniProt, Protein family clans and the Pearson’s correlation with other existing methods. Conclusion: The experimental results exhibited a major supremacy of the proposed method over other semantic similarity measures. HIGHLIGHTS:1. An improved approach for semantic similarity evaluation for GO terms based on the information content and the topological factors is developed.2. The proposed method shows highest correlation for MF (Molecular Function) ontology.