Publication Type : Journal Article
Publisher : International Journal of Control Theory and Applications
Source : International Journal of Control Theory and Applications, Volume 9, Number 10, p.4211-4219 (2016)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989257155&partnerID=40&md5=6d98b4c8e273972aa8d1b11478ff9793
Year : 2016
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.
Cite this Research Publication : L. Aswathy R. Menon, SuryaPrabha, B., Ashok, S., and Judy, M. V., “Application of ant colony optimization in identifying the key gene interactions”, International Journal of Control Theory and Applications, vol. 9, pp. 4211-4219, 2016.