System Modeling in Cellular Biology

by Szallasi, Zoltan; Stelling, Jorg; Periwal, Vipul

• ISBN13: 9780262514224
• ISBN10: 0262514222
• Format: Paperback
• Copyright: 2010-03-31
• Publisher: Mit Pr

Summary

Research in systems biology requires the collaboration of researchers from diverse backgrounds, including biology, computer science, mathematics, statistics, physics, and biochemistry. These collaborations, necessary because of the enormous breadth of background needed for research in this field, can be hindered by differing understandings of the limitations and applicability of techniques and concerns from different disciplines. This comprehensive introduction and overview of system modeling in biology makes the relevant background material from all pertinent fields accessible to researchers with different backgrounds. The emerging area of systems level modeling in cellular biology has lacked a critical and thorough overview. This book fills that gap. It is the first to provide the necessary critical comparison of concepts and approaches, with an emphasis on their possible applications. It presents key concepts and their theoretical background, including the concepts of robustness and modularity and their exploitation to study biological systems; the best-known modeling approaches, and their advantages and disadvantages; lessons from the application of mathematical models to the study of cellular biology; and available modeling tools and datasets, along with their computational limitations.

Table of Contents

Preface	p. vii
General Concepts
The Role of Modeling in Systems Biology	p. 3
Complexity and Robustness of Cellular Systems	p. 19
On Modules and Modularity	p. 41
Modeling Approaches
Bayesian Inference of Biological Systems: The Logic of Biology	p. 53
Stoichiometric and Constraint-based Modeling	p. 73
Modeling Molecular Interaction Networks with Nonlinear Ordinary Differential Equations	p. 97
Qualitative Approaches to the Analysis of Genetic Regulatory Networks	p. 125
Stochastic Modeling of Intracellular Kinetics	p. 149
Kinetics in Spatially Extended Systems	p. 177
Models And Reality
Biological Data Acquisition for System Level ModelingùAn Exercise in the Art of Compromise	p. 201
Methods to Identify Cellular Architecture and Dynamics from Experimental Data	p. 221
Using Control Theory to Study Biology	p. 243
Synthetic Gene Regulatory Systems	p. 269
Multilevel Modeling in Systems Biology: From Cells to Whole Organs	p. 297
Computational Modeling
Computational Constraints on Modeling in Systems Biology	p. 315
Numerical Simulation for Biochemical Kinetics	p. 331
Software Infrastructure for Effective Communication and Reuse of Computational Models	p. 355
A Software Tools for Biological Modeling	p. 379
References	p. 385
Contributors	p. 435
Index	p. 439
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