Mining for novel tumor suppressor genes using a shortest path approach.

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 Dyn

authors

Chen L,Yang J,Huang T,Kong X,Lu L,Cai YD

doi

10.1080/07391102.2015.1042915

subject

Has Abstract

pub_date

2016-01-01 00:00:00

pages

664-75

issue

3

eissn

0739-1102

issn

1538-0254

journal_volume

34

pub_type

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