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BioMed Research International
Volume 2014 (2014), Article ID 371397, 9 pages
http://dx.doi.org/10.1155/2014/371397
Research Article

Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network

1Colorectal Surgery Department, China-Japan Union Hospital of Jilin University, Changchun 130033, China
2State Key Laboratory of Medical Genomics, Institute of Health Sciences, Chinese Academy of Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Shanghai 200025, China
3Breast and Thyroid Surgery Department, The Second Hospital of Jilin University, Changchun 130041, China
4Colorectal Surgery Department, The Second Hospital of Jilin University, Changchun 130041, China

Received 29 December 2013; Accepted 3 February 2014; Published 5 March 2014

Academic Editor: Tao Huang

Copyright © 2014 Yang Jiang 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.

Supplementary Material

The Supplementary Material consists of four files. In detail, Supplementary Material 1 lists 150 gastric cancer related genes; Supplementary Material 2 lists the shortest path genes and their permutation FDRs; Supplementary Material 3 lists GO enrichment results of 144 genes; Supplementary Material 4 lists KEGG enrichment results of 144 genes.

  1. Supplementary Material 1
  2. Supplementary Material 2
  3. Supplementary Material 3
  4. Supplementary Material 4