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BioMed Research International
Volume 2014, Article ID 416323, 10 pages
http://dx.doi.org/10.1155/2014/416323
Review Article

Approaches for Recognizing Disease Genes Based on Network

1School of Information Science and Technology, Xiamen University, Xiamen 361005, China
2School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

Received 6 December 2013; Revised 6 January 2014; Accepted 9 January 2014; Published 24 February 2014

Academic Editor: Tao Huang

Copyright © 2014 Quan Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Diseases are closely related to genes, thus indicating that genetic abnormalities may lead to certain diseases. The recognition of disease genes has long been a goal in biology, which may contribute to the improvement of health care and understanding gene functions, pathways, and interactions. However, few large-scale gene-gene association datasets, disease-disease association datasets, and gene-disease association datasets are available. A number of machine learning methods have been used to recognize disease genes based on networks. This paper states the relationship between disease and gene, summarizes the approaches used to recognize disease genes based on network, analyzes the core problems and challenges of the methods, and outlooks future research direction.