Constructing disease-specific gene networks using pair-wise relevance metric: Application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements

doi:10.1186/1752-0509-2-72

BMC Systems Biology

Volume 2

Viewing options:

Abstract
Full text
PDF (2.6MB)
Additional files

Associated material:

Related literature:

Articles citing this article
on BioMed Central
on Google Scholar
on ISI Web of Science
on PubMed Central
Other articles by authors
on Google Scholar

Jiang W
Li X
Rao S
Wang L
Du L
Li C
Wu C
Wang H
Wang Y
Yang B

on PubMed

Jiang W
Li X
Rao S
Wang L
Du L
Li C
Wu C
Wang H
Wang Y
Yang B
Related articles/pages
on Google

on Google Scholar

on PubMed

Tools:

Post to:

Research article

Constructing disease-specific gene networks using pair-wise relevance metric: Application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements

Wei Jiang¹^* , Xia Li¹^,2^* , Shaoqi Rao¹^,2^,3^,4 , Lihong Wang¹ , Lei Du¹ , Chuanxing Li¹ , Chao Wu¹ , Hongzhi Wang⁵ , Yadong Wang⁵ and Baofeng Yang¹

¹College of Bioinformatics Science and Technology and Bio-pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150081, PR China

²Department of Bioinformatics, Capital University of Medical Sciences, Beijing 100084, PR China

³Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, PR China

⁴Department of Molecular Cardiology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio 44195, USA

⁵Department of Computer Science, Harbin Institute of Technology, Harbin 150080, PR China

author email corresponding author email* Contributed equally

BMC Systems Biology 2008, 2:72doi:10.1186/1752-0509-2-72


Published:	10 August 2008

Additional files

Additional file 1:

The AFV values of the 200 colon cancer-specific gene interactions.

Format: PDF Size: 43KB Download file

This file can be viewed with: Adobe Acrobat Reader

Additional file 2:

Application of the novel network approach to prostate cancer microarray data.

Format: PDF Size: 253KB Download file

This file can be viewed with: Adobe Acrobat Reader