- ISBN 10: 0387262873
- ISBN 13: 9780387262871
Computational and Statistical Approaches to Genomics, 2nd Edition, aims to help researchers deal with current genomic challenges. During the three years after the publication of the first edition of this book, the computational and statistical research in genomics have become increasingly more important and indispensable for understanding cellular behavior under a variety of environmental conditions and for tackling challenging clinical problems. In the first edition, the organizational structure was: data à analysis à synthesis à application. In the second edition, the same structure remains, but the chapters that primarily focused on applications have been deleted.
This decision was motivated by several factors. Firstly, the main focus of this book is computational and statistical approaches in genomics research. Thus, the main emphasis is on methods rather than on applications. Secondly, many of the chapters already include numerous examples of applications of the discussed methods to current problems in biology.
The range of topics have been broadened to include newly contributed chapters on topics such as alternative splicing, tissue microarray image and data analysis, single nucleotide polymorphisms, serial analysis of gene expression, and gene shaving. Additionally, a number of chapters have been updated or revised.
This book is for any researcher, in academia and industry, in biology, computer science, statistics, or engineering involved in genomic problems. It can also be used as an advanced level textbook in a course focusing on genomic signals, information processing, or genome biology.
Seventeen contributions cover a wide range of topics and span a number of disciplines such as image analysis, statistics, machine learning, pattern recognition, time-frequency and nonlinear signal processing, parallel computing, molecular biology, and others. Each chapter follows the various stages from data and analysis through synthesis and application. Topics include an overview of the role of supercomputers and other tools; approaches to the global modeling and analysis of gene regulatory networks and transcriptional control; state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning; crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels; and biological and medical implications of genomics research. Appropriate for use as an advanced level textbook, as well as for researchers. Edited by Zhang and Shmulevich (U. of Texas M.D. Anderson Cancer Center). Annotation c. Book News, Inc., Portland, OR (booknews.com)
- Publisher: Springer-Verlag New York, LLC
- Format: Hardcover
- Edition: 2nd
- Date Published: May 2006
- Authors: Wei Zhang, Ilya Shmulevich