Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications book cover

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Author(s): Xiaohua Hu (Author), Yi Pan (Author)

  • Publisher: Wiley-Interscience
  • Publication Date: June 22, 2007
  • Edition: 1st
  • Language: English
  • Print length: 424 pages
  • ISBN-10: 047177796X
  • ISBN-13: 9780471777960

Book Description

The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.

Editorial Reviews

Review

“…is an educational and interesting read and a reminder of just how much the worlds of statistics, biology, and computer science have melded.” (Journal of the American Statistical Association, June 2008)

“…a worthwhile read for any bioinformatician and fulfills its stated object of presenting cutting-edge research topics.” (IEEE Engineering in Medicine and Biology Magazine, January/February 2008)

“…this book is essential reading for all researchers in bioinformatics.” (Bioautomation, volume 7)

From the Inside Flap

Wiley Series on Bioinformatics: Computational Techniques and Engineering

Discover how data mining is fueling new discoveries in bioinformatics

As the field of bioinformatics continues to flourish, producing enormous amounts of new data, the need for sophisticated methods of data mining to better manage and extract meaning from bioinformatics data has grown tremendously. This pioneering text brings together an unparalleled group of leading experts in both data mining and bioinformatics. These experts present a broad range of novel methods, techniques, and applications of data mining for the analysis and management of bioinformatics data sets. Among the topics covered are:

  • RNA and protein structure analysis

  • DNA computing

  • Sequence mapping and genome comparison

  • Gene expression data mining

  • Metabolic network modeling

  • Phyloinformatics

  • Biomedical literature data mining

  • Biological data integration and searching

For each topic, readers get an inside perspective into the latest research—what works and what doesn’t and where additional research and development is needed. References to the primary literature facilitate further in-depth research.

Data mining in bioinformatics holds the promise of solving such fundamental problems as protein structure, gene finding, data retrieval, and integration. This text is therefore essential reading for all researchers in bioinformatics, pointing them to new methods and techniques that may be the key to new and important discoveries.

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