High-order/variable-order dynamic Bayesian networks and dynamic qualitative probabilistic networks --- new models of gene regulatory networks

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Network Systems Biology (NSB) is an emerging area focusing on the study of various types of biomolecular networks, such as Gene Regulatory Networks (GRNs), Transcriptional Regulatory Networks (TRNs), Drug Gene Regulatory Networks (DGNs), Protein Interaction Networks (PPIs and DDIs), Metabolic Networks, and Signaling Pathways Networks. The goal of NSB research is to gain biological knowledge and obtain an understanding of the mechanisms of cellular systems and processes, through analyzing and mining the different molecular interactions, and on the basis of the networked data generated from high-throughput technologies. Sophisticated computational methods are required to reconstruct GRNs from gene expression time-series data or to analyze large biomolecular networks, for instance. The task of NSB research is made difficult by the highly diverse set of biomolecules and the complexity of their interactions, the large size and high-dimensionality of high-throughput data sets often containing imprecision, uncertainty or noise in measurements, or small number of samples or time-points.