How new modeling techniques can be used to explore functionally relevant molecular and cellular relationships.

This book serves as an introduction to the myriad computational approaches to gene regulatory modeling and analysis, and is written specifically with experimental biologists in mind. Mathematical jargon is avoided and explanations are given in intuitive terms. In cases where equations are unavoidable, they are derived from first principles or, at the very least, an intuitive description is provided. Extensive examples and a large number of model descriptions are provided for use in both classroom exercises as well as self-guided exploration and learning. As such, the book is ideal for self-learning and also as the basis of a semester-long course for undergraduate and graduate students in molecular biology, bioengineering, genome sciences, or systems biology.

The rapidly developing methods of systems biology can help investigators in various areas of modern biomedical research to make inference and predictions from their data that intuition alone would not discern. Many of these methods, however, are commonly perceived as esoteric and inaccessible to biomedical researchers: Even evaluating their applicability to the problem at hand seems to require from the biologist a broad kno- edge of mathematics or engineering. This book is written by scientists who do possess such knowledge, who have successfully applied it to biological problems in various c- texts, and who found that their experience can be crystallized in a form very similar to a typical biological laboratory protocol. Learning a new laboratory procedure may at first appear formidable, and the int- ested researchers may be unsure whether their problem falls within the area of applicability of the new technique. The researchers will rely on the experience of others who have condensed it into a methods paper, with the theory behind the method, its step-by-step implementation, and the pitfalls explained thoroughly and from the practical angle. It is the intention of the authors of this book to make the methods of systems biology widely understood by biomedical researchers by explaining them in the same proven format of a protocol article.

Rovereto,December2002 CorradoPriami ProgrammeCommitteeofCMSB 2003 CorradoPriami(Chair),UniversityofTrento(Italy), CharlesAu?ray,CNRS,Villejuif(France), CosimaBaldari,Universit`adiSiena(Italy), AlexanderBockmayr,Universit ́eHenriPoincar ́e(France), LucaCardelli,MicrosoftResearchCambridge(UK), VincentDanos,Universit ́eParisVII(France), PierpaoloDegano,Universitad ` iPisa(Italy), Francois ̧ Fages,INRIA,Rocquencourt(France), DrabløsFinn,NorwegianUniversityofScienceandTechnology,Trondheim(N- way), MonikaHeiner,BrandenburgUniversityofTechnologyatCottbus(Germany), InaKoch,UniversityofAppliedSciencesBerlin,(Germany), JohnE.

The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry.