	Introduction to Computational Biology: Maps, Sequences and Genomes (Interdisciplinary Statistics) by Michael S. Waterman (Author) Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from...
	Statistical Analysis of Gene Expression Microarray Data by Terry Speed (Editor) Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies. And there is arguably no group better qualified to do so than the authors of this book.Statistical Analysis of Gene Expression Microarray Data...
	An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology) by Uri Alon (Author) Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological...

EDITORIAL REVIEWS

Product Description
Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective. Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications.While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.

CUSTOMER REVIEWS (Average Customer Rating: 4.0 based on 1 review)

Correct title: Stochastic modeling of biological systems by DataGuru (DC)

4 Stars
May 10, 2006
This is one of several recent books with system biology in the title, but first book with emphasis on statistics and stochastic approach. The book discusses some simple math models for biological systems, mostly biochemical models. Main focus is on statistical issues in differentail modeling, those as discussed in the nice Bower and Bolouri (2000) book Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology), and the strong point is the use of Bayesian Markov chain Monte Carlo method for stochastic modeling. Weakness is that, the systems considered are too low-dimensional, and there is a long way toward real system biology issues, which will likely be much more complex, and involve potentially many high-dimensional interactions. Overall, it is simply a very straightforward introductory book, lacks depth and breadth. However, it should serve as a good starting point for people who want to learn something about stat and probabilistic methods relevant to bios system modelling.

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	An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology) by Uri Alon (Author) Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological...
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	Chemical Biophysics: Quantitative Analysis of Cellular Systems (Cambridge Texts in Biomedical Engineering) by Daniel A. Beard (Author), Hong Qian (Author) Chemical Biophysics provides an engineering-based approach to biochemical system analysis for graduate level courses on systems biology, computational bioengineering and molecular biophysics. It is the first textbook to apply rigorous physical chemistry principles to mathematical and computational modeling of biochemical systems for an interdisciplinary audience. The book is structured to show the student the basic biophysical concepts before applying this theory to computational modeling and...
	Computational Systems Biology by Andres Kriete (Editor), Roland Eils (Editor) Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts. This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers...