Publication

Abstract : Optimization is necessary to ensure the quality of data and to strengthen the validity of standardized results in making decision. Diverse research works on meta-heuristic for optimization is recently becoming popular among researchers. Various optimization techniques can be applied to extract and explore meaningful information from high dimensional dataset. In this paper, Ant Colony Optimization (ACO) method is used to optimize the gene similarity network path and forming functional clusters of genes from a semantic similarity graph derived using Gene ontology. The results are promising when compared with the standard benchmark community detection algorithm. © International Science Press.