Methods of Microarray Data Analysis II

Name: Methods of Microarray Data Analysis II
Brand: Springer-Verlag New York Inc.
SKU: 9781402071119
Price: 470.91 PLN
Availability: InStock

Autor: Simon M. Lin, Kimberly F. Johnson

Język:

Oprawa: Twarda

Wydawca: Springer-Verlag New York Inc.

Dostępność: Dostępna u dostawcy w małych ilościach

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Microarray technology is a major experimental tool for functional genomic explorations, and will con...

Informacje o książce

Autor

Simon M. Lin, Kimberly F. Johnson

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2002

strony

214

EAN

9781402071119

ISBN

1402071116

Enbook ID

01417768

Wydawca

Springer-Verlag New York Inc.

Waga

1110

Wymiary

155 x 235 x 20

Pełny opis

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 II is the second book in this pioneering series 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 II focuses on a single data set, 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.

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