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Discovering Cancer Genes by Integrating Network and Functional Properties by Li Li; Kangyu Zhang; James Lee; Shaun Cordes; David P Davis; Zhijun Tang is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Discovering Cancer Genes by Integrating Network and Functional Properties about?

## Abstract ## Background Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes. ## Methods Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1. ## Results Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, pr

Who reads Discovering Cancer Genes by Integrating Network and Functional Properties?

Author

Li Li; Kangyu Zhang; James Lee; Shaun Cordes; David P Davis; Zhijun Tang

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, [2008]-; Springer Science and Business Media LLC (ISSN 1755-8794)

Published

2009

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)