Biological Data Mining

Author:   Jake Y. Chen (Indiana University-Purdue University, Indianapolis, USA) ,  Stefano Lonardi (University of California, Riverside, USA)
Publisher:   Taylor & Francis Ltd
Volume:   v. 11
ISBN:  

9781420086843


Pages:   734
Publication Date:   01 September 2009
Format:   Hardback
Availability:   In Print   Availability explained
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Biological Data Mining


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Full Product Details

Author:   Jake Y. Chen (Indiana University-Purdue University, Indianapolis, USA) ,  Stefano Lonardi (University of California, Riverside, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Volume:   v. 11
Dimensions:   Width: 15.60cm , Height: 4.30cm , Length: 23.40cm
Weight:   1.133kg
ISBN:  

9781420086843


ISBN 10:   1420086847
Pages:   734
Publication Date:   01 September 2009
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Sequence, Structure, and Function. Genomics, Transcriptomics, and Proteomics. Functional and Molecular Interaction Networks. Literature, Ontology, and Knowledge Integration. Genome Medicine Applications.

Reviews

The book will be useful to those interested in applying data mining to biology. Specialists in interdisciplinary areas will also find the book helpful. Despite the diversity of the topics presented, the editors manage to maintain homogeneity throughout the book. I recommend this book as a valuable resource on biological data mining. The chapters offer a wealth of useful information ! --Computing Reviews, January 2011 ! Chen and Lonardi present in this book a showcase of successful recent projects in the research area where biology, computer science, and statistics intersect. The editors have done a good job of pulling together the work of over 80 authors into a well-typeset product with high-resolution graphics and even several diagrams of proteins. ! The authors leave no stone unturned in terms of topics and techniques. ! There is a veritable alphabet soup of special software employed ! there is something for everyone with an interest in bioinformatics in this book. Make sure your library has a copy, or that you buy one for yourselves. --International Statistical Review (2010), 78, 3


The book will be useful to those interested in applying data mining to biology. Specialists in interdisciplinary areas will also find the book helpful. Despite the diversity of the topics presented, the editors manage to maintain homogeneity throughout the book. I recommend this book as a valuable resource on biological data mining. The chapters offer a wealth of useful information ! --Computing Reviews, January 2011 ! Chen and Lonardi present in this book a showcase of successful recent projects in the research area where biology, computer science, and statistics intersect. The editors have done a good job of pulling together the work of over 80 authors into a well-typeset product with high-resolution graphics and even several diagrams of proteins. ! The authors leave no stone unturned in terms of topics and techniques. ! There is a veritable alphabet soup of special software employed ! there is something for everyone with an interest in bioinformatics in this book. Make sure your library has a copy, or that you buy one for yourselves. --International Statistical Review (2010), 78, 3


Author Information

Jake Y. Chen is an assistant professor of informatics at Indiana University, an assistant professor of computer science at Purdue University, and director of the Indiana Center for Systems Biology and Personalized Medicine. Stefano Lonardi is an associate professor of computer science and engineering at the University of California, Riverside.

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