Izudheen, Sminu and Mathew, Sheena (2013) Cancer gene identification using graph centrality. Current Science, 105 (8). 1143-1148. ISSN 0011-3891

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Abstract

One of the most significant challenges of modern bioinformatics is in the development of computational tools to understand and treat diseases like cancer. So far, a variety of methods have been explored for identifying candidate cancer genes. Since protein interactions carry out most biological processes, we propose an algorithm for identifying cancer genes from graph centrality values of the human protein protein interaction network. The precision and accuracy of the results obtained while applying the method on actual protein protein interaction data assert that it can be used as an effective model to identify novel cancer proteins.

Item Type:	Article
Additional Information:	copyright for this article belongs to M/s Indian Academy of Sciences
Subjects:	Computer Science Multidisciplinary Mathematics Medical Informatics
Divisions:	UNSPECIFIED
Depositing User:	Users 27 not found.
Date Deposited:	19 Aug 2026 11:11
Last Modified:	19 Aug 2026 11:11
URI:	https://npl.csircentral.net/id/eprint/3126

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