Sequence Data Mining

Guozhu Dong

ISBN 10: 1441943528 ISBN 13: 9781441943521

Editorial: Springer US, 2007

Idioma: Ingl�s

Condici�n: Nuevo Encuadernaci�n de tapa blanda

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Descripci�n

152 pages. 9.00x6.00x0.60 inches. In Stock.

N� de ref. del art�culo x-1441943528

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Detalles bibliogr�ficos

T�tulo

Sequence Data Mining

Editor

Springer US

Fecha de publicaci�n

2007

Idioma

Ingl�s

ISBN 10

1441943528

ISBN 13

9781441943521

Encuadernaci�n

Paperback

Estado

Brand New

Cat�logos de vendedores

Acerca de

Sinopsis

This book provides balanced coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This volume fills in the gap, allowing readers to access the state-of-the-art results in one place. Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.

De la contraportada

Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more.

Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place.

Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.

Forward by Professor Jiawei Han, University of Illinois at Urbana-Champaign.

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