Publication Type : Journal Article
Publisher : International Journal of Advanced Trends in Computer Science and Engineering
Source : International Journal of Advanced Trends in Computer Science and Engineering, Volume 8, Issue 4 (2019)
Url : http://www.warse.org/IJATCSE/static/pdf/file/ijatcse12842019.pdf
Keywords : Biological network, Centrality measures. Colon cancer, Human diseases, Social Network
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2019
Abstract : Interrelationship of diseases can be analyzed using a biological network graph. In the Network graph of human diseases, each node represents a disease and interrelationship between the diseases is represented by as an edge. Interrelationship between the diseases represent the commonality in the genes associated with diseases. The size of a node represents the number of genes that are associated with the disease. Representation of such biological network can be used to analyze the way other social networks are analyzed. The proposed work introduces an approach to analyze biological network in terms of social network in which causes of different life-threatening diseases such as colon cancer are identified by using different centrality measures
Cite this Research Publication : A. R. Doke, Garla, N., and Radha D., “Analysis of Human gene - Disease association as a Social network”, International Journal of Advanced Trends in Computer Science and Engineering, vol. 8, no. 4, 2019.