An improved method for scoring protein-protein interactions using semantic similarity within the Gene Ontology

Background: Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs). They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO). Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity. Results: We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS), to compute semantic similarity between GO terms annot...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Shobhit Jain, Gary D. Bader
• Keywords: BMCBI 2010, Protein, Semantic Similarity, Semantic Similarity Measures