Differentiating Cancer from Normal Proteinprotein Interactions Through Network Analysis

dc.contributor.author Sahoo, R.
dc.contributor.author Rani, T. S.
dc.contributor.author Bhavani, S. D.
dc.date.accessioned 2022-03-27T05:50:48Z
dc.date.available 2022-03-27T05:50:48Z
dc.date.issued 2016-03-22
dc.description.abstract Protein-protein interaction networks have been modeled as graphs in the literature. Network analysis to contrast networks corresponding to normal cell versus cancerous cell is carried out in this work. Measures commonly used to analyze social networks like betweenness centrality, assortativity, clique participation, and so on, have been computed for these graphs. These measures successfully retrieved proteins encoded by genes that are significant in the context of cancer growth. Apart from degree distribution analysis that is commonly done, we carry out common subgraph analysis as well as bipartite graph analysis to differentiate the cancer network from normal network. Complete analysis is performed for bone cell and the results are presented.
dc.identifier.citation Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications
dc.identifier.uri 10.1016/B978-0-12-804203-8.00017-1
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/B9780128042038000171
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8250
dc.subject Bipartite graph analysis
dc.subject Community discovery algorithms
dc.subject Subgraph analysis
dc.title Differentiating Cancer from Normal Proteinprotein Interactions Through Network Analysis
dc.type Book. Book Chapter
dspace.entity.type
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