Written with experimental biologists in mind, this uses a minimum of mathematical jargon to introduce computational approaches to gene regulatory modeling and analysis. Suitable for the classroom exercises as well as for self-study, this explains the relationship between computational analysis and biology, what models can and cannot predict, how computational models describe gene regulatory networks, and what graphical representations can tell us. Topics include implicit modeling through interaction network maps, the biochemical bases of gene regulation, single cell models, simplified models through mass action kinetics or through Boolean and multi-valued logic, Bayesian Networks, the relationship between logic and Bayesian Networks, DNA sequences searching, model selection theory, robustness analysis, modules and building blocks, data processing for modeling, and applications of computational modeling. Includes a special section on single cell biology, multi-scale modeling, software engineering challenges, and molecular biology in the discovery phase. Distributed by World Scientific. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)