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2006

Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene

8 years 10 months ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectation maximization (SEM) to model gene relationship. It is well-suited for analyzing the time-series data and can deal with cyclical structures that can not be tackled by static Bayesian network. We applied the new method to learning the regulatory network and the metabolic pathway from Saccharomyces Cerevisiae cell cycle gene expression data. The results show that the proposed method is capable of handling missing values in expression data sets, and the inference accuracy can further be improved. Keyword: Microarrays; Gene regulatory networks; Dynamic Bayesian network; Structural expectation maximization
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where BIOCOMP
Authors Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
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