title: Integrating gene expression and protein-protein interaction network to prioritize cancer-associated genes.
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.
authors: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, PR China. wuchao1984@gmail.com
authors: Chao
authors: C
authors: Wu
authors: Jun
authors: J
authors: Zhu
authors: Xuegong
authors: X
authors: Zhang
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism; D002289:Carcinoma, Non-Small-Cell Lung / Q000235:genetics / Q000378:metabolism; D005260:Female; D015870:Gene Expression; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D052138:Genes, Neoplasm; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics / Q000378:metabolism; D025941:Protein Interaction Mapping