Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2016, Article ID 7861274, 10 pages
Research Article

Analysis of Important Gene Ontology Terms and Biological Pathways Related to Pancreatic Cancer

1Department of Gastroenterology, Ninth People’s Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200011, China
2School of Life Sciences, Shanghai University, Shanghai 200444, China
3Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China

Received 31 May 2016; Revised 18 July 2016; Accepted 7 September 2016

Academic Editor: Yungang Xu

Copyright © 2016 Hang Yin 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.


Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlying this disease. However, it is far from complete. In this study, we tried to extract important gene ontology (GO) terms and KEGG pathways for pancreatic cancer by adopting some existing computational methods. Genes that have been validated to be related to pancreatic cancer and have not been validated were represented by features derived from GO terms and KEGG pathways using the enrichment theory. A popular feature selection method, minimum redundancy maximum relevance, was employed to analyze these features and extract important GO terms and KEGG pathways. An extensive analysis of the obtained GO terms and KEGG pathways was provided to confirm the correlations between them and pancreatic cancer.