This book gives a concise overview of the mathematical foundations of kinetics used in chemistry and systems biology. The analytical and numerical methods used to solve complex rate equations with the widely used deterministic approach will be described, with primary focus on practical aspects important in designing experimental studies and the evaluation of data. The introduction of personal computers transformed scientific attitudes in the last two decades considerably as computational power ceased to be a limiting factor. Despite this improvement, certain time-honored approximations in solving rate equations such as the pre-equilibrium or the steady-state approach are still valid and necessary as they concern the information content of measured kinetic traces. The book shows the role of these approximations in modern kinetics and will also describe some common misconceptions in this field.

Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

This is one of the first books to provide a systematic study of the many stochastic models used in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing system. Examples cover the phage lambda genetic switch, eukaryotic gene expression, noise propagation in gene networks, and more. Most of the text should be accessible to scientists with basic knowledge in calculus and probability theory.

Thisvolumecontainstheproceedingsofthe?rstinternationalmeetingonFormal Methods in Systems Biology, held at Microsoft Research, Cambridge, UK, June 4–5, 2008. While there are several venues that cover computational methods in systems biology,there is to date no single conference that brings together the application of the range of formal methods in biology. Therefore, convening such a meeting could prove extremely productive. The purpose of this meeting was to identify techniques for the speci?cation, development and veri?cation of biological m- els.Italsofocusedonthedesignoftoolstoexecuteandanalyzebiologicalmodels in ways that can signi?cantly advance our understanding of biological systems. As a forum for this discussion we invited key scientists in the area of formal methods to this unique meeting. Although this was a one-o? meeting, we are exploring the possibility of this forming the ?rst of what might become an annual conference. Presentations at the meeting were by invitation only; future meetings are expected to operate on a submission and review basis. The Steering Committee and additional referees reviewed the invited papers. Each submission was evaluated by at least two referees. The volume includes nine invited contributions. Formal Methods in Systems Biology 2008 was made possible by the cont- bution and dedication ofmany people. First of all,we wouldlike to thank allthe authors who submitted papers. Secondly, we would like to thank our additional invited speakers and participants. We would also like to thank the members of the Steering Committee for their valuable comments. Finally, we ackno- edge the help of the administrative and technical sta? at the MicrosoftResearch Cambridge lab.

If biology in the 20th century was characterized by an explosion of new technologies and experimental methods, that of the 21st has seen an equally exuberant proliferation of mathematical and computational methods that attempt to systematize and explain the abundance of available data. As we live through the consolidation of a new paradigm where experimental data goes hand in hand with computational analysis, we contemplate the challenge of fusing these two aspects of the new biology into a consistent theoretical framework. Whether systems biology will survive as a field or be washed away by the tides of future fads will ultimately depend on its success to achieve this type of synthesis. The famous quote attributed to Kurt Lewin comes to mind: "there is nothing more practical than a good theory". This book presents a wide assortment of articles on systems biology in an attempt to capture the variety of current methods in systems biology and show how they can help to find answers to the challenges of modern biology.

The rapid development of efficient computational tools has allowed researchers to tackle biological problems and to predict, analyse and monitor, at an atomic level, molecular recognition processes. This book offers a fresh perspective on how computational tools can aid the chemical biology research community and drive new research. Chapters from internationally renowned leaders in the field introduce concepts and discuss the impact of technological advances in computer hardware and software in explaining and predicting phenomena involving biomolecules, from small molecules to macromolecular systems. Important topics from the understanding of biomolecules to the modification of their functions are addressed, as well as examples of the application of tools in drug discovery, glycobiology, protein design and molecular recognition. Not only are the cutting-the-edge methods addressed, but also their limitations and possible future development. For anyone wishing to learn how computational chemistry and molecular modelling can provide information not easily accessible through other experimental methods, this book will be a valuable resource. It will be of interest to postgraduates and researchers in the biological and chemical sciences, medicinal and pharmaceutical chemistry, and theoretical chemistry.

This book constitutes the proceedings of the 11th International Conference on Computational Methods in Systems Biology, CMSB 2013, held in Klosterneuburg, Austria, in September 2013. The 15 regular papers included in this volume were carefully reviewed and selected from 27 submissions. They deal with computational models for all levels, from molecular and cellular, to organs and entire organisms.

This introductory guide provides a thorough explanation of the mathematics and algorithms used in standard data analysis techniques within systems biology, biochemistry, and biophysics. Each part of the book covers the mathematical background and practical applications of a given technique. Readers will gain an understanding of the mathematical and algorithmic steps needed to use these software tools appropriately and effectively, as well how to assess their specific circumstance and choose the optimal method and technology. Ideal for students planning for a career in research, early-career researchers, and established scientists undertaking interdisciplinary research.