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BioMed Research International
Volume 2014 (2014), Article ID 891945, 8 pages
http://dx.doi.org/10.1155/2014/891945
Research Article

A Graphic Method for Identification of Novel Glioma Related Genes

1Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China
2State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiaotong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200025, China
3Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun 130033, China
4Institute of Systems Biology, Shanghai University, Shanghai 200444, China
5CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China

Received 18 April 2014; Revised 25 May 2014; Accepted 28 May 2014; Published 23 June 2014

Academic Editor: Tao Huang

Copyright © 2014 Yu-Fei Gao 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 contains four files. In detail, Supplementary Material I lists 77 glioma related genes; Supplementary Material II lists 215 candidate genes with betweenness greater than 0 and their permutation FDRs; Supplementary Material III lists KEGG enrichment results of 67 selected genes; Supplementary Material IV lists GO enrichment results of 67 selected genes.

  1. Supplementary Material