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Modularity-based Credible Prediction of Disease Genes and Detection of Disease Subtypes on the Phenotype-gene Heterogeneous Network by Xin Yao; Han Hao; Yanda Li; Shao Li is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Modularity-based Credible Prediction of Disease Genes and Detection of Disease Subtypes on the Phenotype-gene Heterogeneous Network about?

## Background Protein-protein interaction networks and phenotype similarity information have been synthesized together to discover novel disease-causing genes. Genetic or phenotypic similarities are manifested as certain modularity properties in a phenotype-gene heterogeneous network consisting of the phenotype-phenotype similarity network, protein-protein interaction network and gene-disease association network. However, the quantitative analysis of modularity in the heterogeneous network and its influence on disease-gene discovery are still unaddressed. Furthermore, the genetic correspondence of the disease subtypes can be identified by marking the genes and phenotypes in the phenotype-gene network. We present a novel network inference method to measure the network modularity, and in particular to suggest the subtypes of diseases based on the heterogeneous network. ## Results Based on a measure which is introduced to evaluate the closeness between two nodes in the phenotype-gene heterogeneous network, we developed a Hitting-Time-based method, CIPHER-HIT, for assessing the modularity of disease gene predictions and credibly prioritizing disease-causing genes, and then identifying

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Author

Xin Yao; Han Hao; Yanda Li; Shao Li

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, [2006]-; Springer Science and Business Media LLC (ISSN 1752-0509)

Published

2011

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)