gSemSim: Semantic Similarity Measure for Intra Gene Ontology Terms

Gene Ontology (GO) is an important bioinformatics scheme to unify the representation of gene and gene product attributes across all species. Measuring similarity or distance between GO terms is a key step for determining hidden relationship between genes. The notion of similarity between GO terms is a usual step in knowledge discovery related tasks. In literature various similarity measures between GO terms have been proposed. We have introduced a novel similarity measure scheme to improve three conventional similarity measures to reduce their limitations. The salient feature of the proposed GO Semantic Similarity (gSemSim) measure is its ability to show more realistic similarity between concepts in perspective of domain knowledge. A comparative result with other technique has also been presented that showing an improved contextual meaning of the proposed semantic similarity. This study is expected to assist the community of bio informaticians in the selection of better similarity measure required for correct annotations of genes in gene ontology.