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Methods of Microarray Data Analysis: Papers from Camda 00

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ISBN 10: 0792375645 / ISBN 13: 9780792375647
Editorial: Springer
Nuevos Condición: New Encuadernación de tapa dura
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Librería en AbeBooks desde: 21 de mayo de 2012

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Descripción

Hardcover. 189 pages. Dimensions: 9.0in. x 7.0in. x 0.7in.Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques. Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformaticsgenomics courses in undergraduate and graduate programs. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. N° de ref. de la librería 9780792375647

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Detalles bibliográficos

Título: Methods of Microarray Data Analysis: Papers ...

Editorial: Springer

Encuadernación: Hardcover

Condición del libro:New

Tipo de libro: Hardcover

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Sinopsis:

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques.
Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.

About the Author:

Simon M. Lin is Manager of Duke Bioinformatics Shared Resource, Duke University Medical Center. Kimberly F. Johnson is Director of Duke Cancer Center Information Systems and Director of Duke Bioinformatics Shared Resource, Duke University Medical Center.

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