A copula method for modeling directional dependence of genes

Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search s...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap-Hoon Han, Changyi Park, Insuk Sohn
• Keywords: Bayesian Network, Bayesian Network Approach, BMCBI 2008, Gene