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

网络系统生物学（NSB）是一个新兴的领域，专注于研究各种类型的生物分子网络，如基因调控网络（GRNs），转录调控网络（TRNs），药物基因调控网络（DGNs），蛋白质相互作用网络（PPI和DDI），代谢网络和信号通路网络。NSB研究的目标是通过分析和挖掘不同的分子相互作用，并在高通量技术产生的网络数据的基础上，获得生物学知识，并了解细胞系统和过程的机制。例如，需要复杂的计算方法来从基因表达时间序列数据重建GRNs或分析大型生物分子网络。NSB研究的任务由于生物分子的高度多样性及其相互作用的复杂性，高通量数据集的大尺寸和高维性而变得困难，这些数据集通常包含测量中的不精确性，不确定性或噪声，或者少量样品或时间点。

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.