DISCRETE DYNAMIC MODELING OF CELLULAR SIGNALING NETWORKS

被引:49
作者
Albert, Reka [1 ]
Wang, Rui-Sheng [1 ]
机构
[1] Penn State Univ, Dept Phys, University Pk, PA 16802 USA
来源
METHODS IN ENZYMOLOGY: COMPUTER METHODS, PART B | 2009年 / 467卷
关键词
GENETIC REGULATORY NETWORKS; LOGICAL ANALYSIS; QUALITATIVE SIMULATION; TRANSDUCTION PATHWAYS; ARABIDOPSIS-THALIANA; BIOLOGICAL NETWORKS; BOOLEAN NETWORKS; YEAST; INFERENCE; PREDICTS;
D O I
10.1016/S0076-6879(09)67011-7
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.
引用
收藏
页码:281 / 306
页数:26
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