A Non-Homogeneous Dynamic Bayesian Network with Sequentially Coupled Interaction Parameters for Applications in Systems and Synthetic Biology

• Published in: Statistical applications in genetics and molecular biology Vol. 11; no. 4
• Main Authors: Grzegorczyk, Marco, Husmeier, Dirk
• Format: Journal Article
• Language: English
• Published: Germany De Gruyter 12.07.2012
• Subjects: Algorithms; Arabidopsis - genetics; Bayes Theorem; Bayesian multiple changepoint processes; Bayesian regularization; Computational Biology - methods; Computational Biology - statistics & numerical data; Gene Expression Profiling - methods; Gene Expression Profiling - statistics & numerical data; Gene Expression Regulation, Fungal; Gene Expression Regulation, Plant; gene regulatory networks; Gene Regulatory Networks - physiology; Genetic Heterogeneity; Models, Statistical; non-stationary gene expression time series; Oligonucleotide Array Sequence Analysis; reversible jump Markov chain Monte Carlo; Saccharomyces cerevisiae - genetics; Synthetic Biology - methods; Synthetic Biology - statistics & numerical data; Systems Biology - methods; Systems Biology - statistics & numerical data; time varying dynamic Bayesian networks

An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homog...