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Fundamentals of data mining in genomics and proteomics

Author: Werner Dubitzky; Martin Granzow; Daniel P Berrar
Publisher: New York : Springer, ©2007.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Publication:Springer e-books
Summary:
To exploit data obtained from experimental and observational studies, life scientists need to understand the analytical techniques and methods from statistics and data mining. These techniques are not easily accessible to life scientists working on genomics and proteomics problems. This book aims to present these analytical methods.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Fundamentals of data mining in genomics and proteomics.
New York : Springer, ©2007
(DLC) 2006934109
(OCoLC)84922989
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Werner Dubitzky; Martin Granzow; Daniel P Berrar
ISBN: 9780387475097 0387475095 0387475087 9780387475080
OCLC Number: 186568905
Description: 1 online resource (xxii, 281 pages) : illustrations
Contents: Front Matter; Introduction to Genomic and Proteomic Data Analysis; Design Principles for Microarray Investigations; Pre-Processing DNA Microarray Data; Pre-Processing Mass Spectrometry Data; Visualization in Genomics and Proteomics; Clustering --
Class Discovery in the Post-Genomic Era; Feature Selection and Dimensionality Reduction in Genomics and Proteomics; Resampling Strategies for Model Assessment and Selection; Classification of Genomic and Proteomic Data Using Support Vector Machines; Networks in Cell Biology; Identifying Important Explanatory Variables for Time-Varying Outcomes.
Responsibility: edited by Werner Dubitzky, Martin Granzow, Daniel Berrar.

Abstract:

This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics.  Read more...

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