Advanced Data Mining Technologies in Bioinformatics

By: Hui-Huang Hsu (Editor)

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Hardcover | 31 March 2006

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Hardcover
344 Pages

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25.4 x 17.78 x 2.06

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The technologies in data mining have been applied to bioinformatics research in the past few years with success, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays a essential role in understanding the emerging problems in genomics, proteomics, and systems biology. ""Advanced Data Mining Technologies in Bioinformatics"" covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. ""Advanced Data Mining Technologies in Bioinformatics"" is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic.

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You Can Find This Book In

Non-Fiction Computing & I.T.Databases Data Mining Computer Science Science Biology, Life Sciences Biochemistry Education

Introduction to data mining in bioinformatics	p. 1
Hierarchical profiling, scoring and applications in bioinformatics	p. 13
Combinatorial fusion analysis : methods and practices of combining multiple scoring systems	p. 32
DNA sequence visualization	p. 63
Proteomics with mass spectrometry	p. 85
Efficient and robust analysis of large phylogenetic datasets	p. 104
Algorithmic aspects of protein threading	p. 118
Pattern differentiations and formulations for heterogeneous genomic data through hybrid approaches	p. 136
Parameterless clustering techniques for gene expression analysis	p. 155
Joint discriminatory gene selection for molecular classification of cancer	p. 174
A haplotype analysis system for genes discovery of common disease	p. 214
A Bayesian framework for improving clustering accuracy of protein sequences based on association rules	p. 231
In silico recognition of protein-protein interactions : theory and applications	p. 248
Differential association rules : understanding annotations in protein interaction networks	p. 269
Mining bio literature : toward automatic annotation of genes and proteins	p. 283
Comparative genome annotation systems	p. 296
Table of Contents provided by Blackwell. All Rights Reserved.

Advanced Data Mining Technologies in Bioinformatics

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Hardcover

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