A hybrid approach to gene ranking using gene relation networks derived from literature for the identification of disease gene markers
by Miyoung Shin; Hyungmin Lee; Munpyo Hong
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 6, No. 3, 2012

Abstract: For the identification of gene markers involved in diseases, microarray expression profiles have been widely used to prioritize genes. In this paper, we propose a novel approach to gene ranking that employs gene relation network derived from literature along with microarray expression scores to calculate ranking statistics of individual genes. In particular, the gene relation network is constructed from literature by applying syntactic analysis and co-occurrence method in a hybrid manner. For evaluation, the proposed method was tested with publicly available prostate cancer data. The result shows that our method is superior to other existing approaches.

Online publication date: Wed, 17-Dec-2014

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