o f t i t l e s , v i s i t u s a t w w w. c r c p r e s s . c o m Textbook
An Introduction to Systems Biology
Textbook
Introduction to Bioinformatics Anna Tramontano
Uri Alon
University of Rome La Sapienza, Italy
Harvard Medical School, Boston MA, USA
Series: Chapman & Hall/CRC Mathematical & Computational Biology, 13
Series: Chapman & Hall/CRC Mathematical & Computational Biology, 10
From the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, Introduction to Bioinformatics describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. The author addresses the ways to store and retrieve biological data, decrypt information encoded by genomes, and detect and exploit the evolutionary and functional relationships among biological elements. The book also includes material on proteomics that is not found in any other basic bioinformatics textbook. It concludes with a discussion of the future of bioinformatics.
This book presents recently discovered design principles that govern the structure and behavior of biological networks such as gene circuits, highlighting simple, recurring circuit elements that make up the network. It provides a quantitative theory for which circuits are found in a given environment and a mathematical framework for understanding and even designing biological circuits. The book requires only basic mathematics understanding and includes a review of the necessary background material. It fills a significant need for a textbook and introduction to the concepts, principles, and mathematical tools that will form the basis of future developments in the field.
Catalog no. C5696, ISBN: 978-1-58488-569-6 2007, 6-1/8 x 9-1/4, 192 pp., Soft Cover Suggested Price: $62.95 / £34.99
Catalog no. C6420, ISBN: 978-1-58488-642-6 2007, 7 x 10, 320 pp., Soft Cover Suggested Price: $57.95 / £31.99
Bioinformatics
Design Principles of Biological Circuits
Textbook
Introduction to Machine Learning and Bioinformatics Sushmita Mitra, Sujay Datta, Theodore Perkins, and George Michailidis
Kinetic Modelling in Systems Biology 119
Oleg Demin
Moscow State University, Russia
Igor Goryanin
University of Edinburgh, Scotland, UK
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Series: Chapman & Hall/CRC Mathematical & Computational Biology, 19
Examining the connections between these two increasingly intertwined areas, this text presents a unifying, thorough, and accessible introduction to the basic ideas and latest developments in machine learning and bioinformatics. It describes the major problems in bioinformatics and the concepts and algorithms of machine learning. The authors demonstrate the capabilities of key machine learning techniques, such as hidden Markov models and artificial neural networks, and apply state-of-the-art techniques to bioinformatics problems in structural biology, cancer treatment, and proteomics. They also include exercises at the end of some chapters and offer instructional materials on their website.
Focusing on one of the main pillars in the future development of systems biology, this book explores the kinetic modeling approach and how to apply it to solve real-life problems. It covers model creation techniques, model verification and validation, and simulations and interpretation of biological results. The authors describe underlying algorithms for selected reference methods and present several examples of applications, ranging from drug safety mechanisms to multiple target identification analysis to optimization of E. coli amino acid biosynthesis. The accompanying CD-ROM contains pathway diagrams, model examples, EPE software, and DBSolve installation.
Catalog no. C682X, ISBN: 978-1-58488-682-2 2008, 6-1/8 x 9-1/4, 384 pp. Suggested Price: $79.95 / £39.99
Catalog no. C6676, ISBN: 978-1-58488-667-9 January 2009, 6-1/8 x 9-1/4, 360 pp. Suggested Price: $79.95 / £44.99
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CATBMS_K00164_2009 Cat.indd 119
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