
Biological Data Mining
Chapman & Hall/CRC (Publisher)
1st Edition
Published on 1. September 2009
Book
Hardback
734 pages
978-1-4200-8684-3 (ISBN)
Description
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics.
The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications.
This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.
The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications.
This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.
Reviews / Votes
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
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional
Product notice
Paper over boards
Illustrations
169 s/w Abbildungen, 69 s/w Tabellen
69 Tables, black and white; 169 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Weight
1133 gr
ISBN-13
978-1-4200-8684-3 (9781420086843)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jake Y. Chen | Stefano Lonardi
Biological Data Mining
Book
06/2017
1st Edition
CRC Press
€120.40
Shipment within 10-20 days

Jake Y. Chen | Stefano Lonardi
Biological Data Mining
E-Book
09/2009
1st Edition
Chapman & Hall/CRC
€109.99
Available for download

Jake Y. Chen | Stefano Lonardi
Biological Data Mining
E-Book
09/2009
Chapman and Hall
€109.99
Available for download
Persons
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.
Stefano Lonardi is an associate professor of computer science and engineering at the University of California, Riverside.
Content
Sequence, Structure, and Function. Genomics, Transcriptomics, and Proteomics. Functional and Molecular Interaction Networks. Literature, Ontology, and Knowledge Integration. Genome Medicine Applications.