Computational and Statistical Approaches to Genomics

Zhang, Wei|Shmulevich, Ilya

ISBN 10: 1441938826 / ISBN 13: 9781441938824

Published by Springer US, 2010

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains the newest research results on genomic analysis and modeling using state-of-the-art methods from engineering, statistics, and genomicsInvolves the application of these tools and models to real biological and clinical problemsProvid. Seller Inventory # 4174252

Bibliographic Details

Title: Computational and Statistical Approaches to ...

Publisher: Springer US

Publication Date: 2010

Binding: Soft cover

Condition: New

Edition: 2nd Edition

About this title

Synopsis:

The second edition of this book adds eight new contributors to reflect a modern cutting edge approach to genomics. It contains the newest research results on genomic analysis and modeling using state-of-the-art methods from engineering, statistics, and genomics. These tools and models are then applied to real biological and clinical problems. The book’s original seventeen chapters are also updated to provide new initiatives and directions.

From the Back Cover:

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.