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Machine learning approaches to bioin...

Yang, Zheng Rong.{me_controlnum}

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Machine learning approaches to bioinformatics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning approaches to bioinformatics/ Zheng Rong Yang.
Author:	Yang, Zheng Rong.{me_controlnum}
Published:	Singapore ;World Scientific Pub. Co., : c2010.,
Description:	xiv, 322 p. :ill. (some col.)
Subject:	Bioinformatics. -
Online resource:	http://www.worldscientific.com/worldscibooks/10.1142/7454#t=toc
ISBN:	9789814287319 (electronic bk.)

Machine learning approaches to bioinformatics
Yang, Zheng Rong.{me_controlnum}

Machine learning approaches to bioinformatics[electronic resource] /Zheng Rong Yang. - Singapore ;World Scientific Pub. Co.,c2010. - xiv, 322 p. :ill. (some col.) - Science, engineering, and biology informatics ;v. 4. - Science, engineering, and biology informatics ;v. 4..

Includes bibliographical references (p. 279-317) and index.

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers to follow the existing procedures in individual research. Unlike most of the bioinformatics books on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for teaching purposes. An essential reference for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects.

Electronic reproduction.
Singapore :
World Scientific Publishing Co.,
2010.

System requirements: Adobe Acrobat Reader.

ISBN: 9789814287319 (electronic bk.)Subjects--Topical Terms:

553671
Bioinformatics.

LC Class. No.: QH324.25

Dewey Class. No.: 572.80285

Machine learning approaches to bioinformatics
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504 $a Includes bibliographical references (p. 279-317) and index.
520 $a This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers to follow the existing procedures in individual research. Unlike most of the bioinformatics books on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for teaching purposes. An essential reference for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects.
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