Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach
Joint Authors
Zhou, You
Yang, Jing
Lu, Changhong
Wang, Meng
Wu, Kai
Cai, Yu-Dong
Yuan, Fei
Kong, Xiangyin
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system.
Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments.
The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease.
In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network.
The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions.
Many of the obtained genes and chemicals are associated with prostate cancer.
American Psychological Association (APA)
Yuan, Fei& Zhou, You& Wang, Meng& Yang, Jing& Wu, Kai& Lu, Changhong…[et al.]. 2015. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057907
Modern Language Association (MLA)
Yuan, Fei…[et al.]. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057907
American Medical Association (AMA)
Yuan, Fei& Zhou, You& Wang, Meng& Yang, Jing& Wu, Kai& Lu, Changhong…[et al.]. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057907
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057907