A framework for identifying colorectal cancer genes in detected protein complexes
by Xiwei Tang; Mingcai Zheng; Bihai Zhao; Guosheng Huang
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 22, No. 3, 2019

Abstract: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and has been the fourth leading cause of cancer-related death worldwide. Inherited factors have a significant role in the CRC growth and progression. Identification of mutation genes leading to CRC remains an arduous task. Compared with the biologically experimental technologies for detecting potential CRC genes, the computational methods are more worthwhile and more efficient. In the study, a new method called ICGPC is proposed to discover latent CRC susceptibility genes. ICGPC takes full advantage of all kinds of biological information closely related to CRC like protein-protein interactions, Sub-Cellular Localisation (SCL) and protein complexes. ICGPC discovers a list of potential proteins encoded by CRC-causal genes. The literature study method is used to evaluate the top proteins in the list and determine that out of 30 novel proteins, 10 proteins are closely associated to CRC. Especially, the top five proteins, i.e., PCNA, CDC20, CCNB1, FZR1 and CDC27, are the most promising candidates and biologists should pay more attention to them.

Online publication date: Fri, 05-Jul-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com