Modeling oncology gene pathways network with multiple genotypes and phenotypes via a copula method

Le Bao, Zhou Zhu, Jingjing Ye

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Identification of interactions between molecular features (e.g. mutation, gene expression change) and gross phenotypes in diseases and other biological processes is one of the important challenges in genomic research. Popular approaches such as GSEA are limited to hypothesis tests of bivariate association. However, a specific phenotype is often dependent upon multiple molecular features. It is thus worth considering all possible interactions jointly for a more precise and realistic representation of the cellular network. In this article, a semiparametric copula model is developed to jointly model genotypes, pathways and phenotypes to accomplish this object. A two-step procedure for reconstruction of the network is described. Simulation studies indicate that the method is effective and accurate for the network reconstruction. Application using NCI60 cancer cell line data identifies several subsets of molecular features that jointly perform as the predictors of clinical phenotypes. The copula model is expected to have a broad impact on biomedical research, ranging from cancer treatment to disease prevention.

Original languageEnglish (US)
Title of host publication2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings
Pages237-246
Number of pages10
DOIs
StatePublished - 2009
Event2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Nashville, TN, United States
Duration: Mar 30 2009Apr 2 2009

Publication series

Name2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings

Other

Other2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009
Country/TerritoryUnited States
CityNashville, TN
Period3/30/094/2/09

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • Artificial Intelligence
  • Computational Theory and Mathematics

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