Abstract:
:Cancer, being among the most serious diseases, causes many deaths every year. Many investigators have devoted themselves to designing effective treatments for this disease. Cancer always involves abnormal cell growth with the potential to invade or spread to other parts of the body. In contrast, tumor suppressor genes (TSGs) act as guardians to prevent a disordered cell cycle and genomic instability in normal cells. Studies on TSGs can assist in the design of effective treatments against cancer. In this study, we propose a computational method to discover potential TSGs. Based on the known TSGs, a number of candidate genes were selected by applying the shortest path approach in a weighted graph that was constructed using protein-protein interaction network. The analysis of selected genes shows that some of them are new TSGs recently reported in the literature, while others may be novel TSGs.
journal_name
J Biomol Struct Dynjournal_title
Journal of biomolecular structure & dynamicsauthors
Chen L,Yang J,Huang T,Kong X,Lu L,Cai YDdoi
10.1080/07391102.2015.1042915subject
Has Abstractpub_date
2016-01-01 00:00:00pages
664-75issue
3eissn
0739-1102issn
1538-0254journal_volume
34pub_type
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