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Open Access Highly Accessed Methodology article

Integrating gene expression and protein-protein interaction network to prioritize cancer-associated genes

Chao Wu12*, Jun Zhu2 and Xuegong Zhang1

Author Affiliations

1 MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084 PR, China

2 Sage Bionetworks, Seattle, Washington, USA

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BMC Bioinformatics 2012, 13:182  doi:10.1186/1471-2105-13-182

Published: 28 July 2012

Abstract

Background

To understand the roles they play in complex diseases, genes need to be investigated in the networks they are involved in. Integration of gene expression and network data is a promising approach to prioritize disease-associated genes. Some methods have been developed in this field, but the problem is still far from being solved.

Results

In this paper, we developed a method, Networked Gene Prioritizer (NGP), to prioritize cancer-associated genes. Applications on several breast cancer and lung cancer datasets demonstrated that NGP performs better than the existing methods. It provides stable top ranking genes between independent datasets. The top-ranked genes by NGP are enriched in the cancer-associated pathways. The top-ranked genes by NGP-PLK1, MCM2, MCM3, MCM7, MCM10 and SKP2 might coordinate to promote cell cycle related processes in cancer but not normal cells.

Conclusions

In this paper, we have developed a method named NGP, to prioritize cancer-associated genes. Our results demonstrated that NGP performs better than the existing methods.