Combining Instantaneous and Time-Delayed Interactions between Genes - A Two Phase Algorithm Based on Information Theory

被引：0
作者：
Morshed, Nizamul [1 ]
Chetty, Madhu [1 ]
机构：
[1] Monash Univ, Clayton, Vic 3800, Australia
来源：
AI 2011: ADVANCES IN ARTIFICIAL INTELLIGENCE | 2011年 / 7106卷
关键词：
Information theory; Bayesian network; Gene regulatory network; BAYESIAN NETWORKS; INFERENCE; ARACNE;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Understanding the way how genes interact is one of the fundamental questions in systems biology. The modeling of gene regulations currently assumes that genes interact either instantaneously or with a certain amount of time delay. In this paper, we propose an information theory based novel two-phase gene regulatory network (GRN) inference algorithm using the Bayesian network formalism that can model both instantaneous and single-step time-delayed interactions between genes simultaneously. We show the effectiveness of our approach by applying it to the analysis of synthetic data as well as the Saccharomyces cerevisiae gene expression data.
引用
收藏
页码：102 / 111
页数：10
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