Application of the Shortest Path Algorithm for the Discovery of Breast Cancer-Related Genes

Author(s): Lei Chen, Zhi Hao Xing, Tao Huang, Yang Shu, GuoHua Huang, Hai-Peng Li*.

Journal Name: Current Bioinformatics

Volume 11 , Issue 1 , 2016

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Abstract:

Breast cancer, the most prevalent cancer in women, develops from breast tissue. Its incidence has increased in recent years due to environmental risk factors. Thus, it is urgent to uncover the mechanism underlying breast cancer to design effective treatments. Identification of all breast cancer-related genes is one way to help elucidate the underlying breast cancer mechanism. In this study, a computational method was built and applied to discover new candidate breast cancer-related genes. Based on the known breast cancer-related genes retrieved from public databases, the shortest path algorithm was applied to discover new candidate genes in the protein-protein interaction network. The analysis results of the selected genes suggest that some of them are deemed breast cancer-related genes according to the most recent published literature, while others have direct or indirect associations with the initiation and development of breast cancer.

Keywords: Betweenness, breast cancer, disease gene, protein-protein interaction, shortest path algorithm, weighted network.

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Article Details

VOLUME: 11
ISSUE: 1
Year: 2016
Page: [51 - 58]
Pages: 8
DOI: 10.2174/1574893611666151119220024

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