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Methods Of Microarray Data Analysis Ii Papers From Camda 01 1st Edition Simon M Lin

  • SKU: BELL-4591990
Methods Of Microarray Data Analysis Ii Papers From Camda 01 1st Edition Simon M Lin
$ 31.00 $ 45.00 (-31%)

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Methods Of Microarray Data Analysis Ii Papers From Camda 01 1st Edition Simon M Lin instant download after payment.

Publisher: Springer US
File Extension: PDF
File size: 5.18 MB
Pages: 214
Author: Simon M. Lin, Kimberly F. Johnson (eds.)
ISBN: 9780306475986, 9781402071119, 0306475987, 1402071116
Language: English
Year: 2002
Edition: 1

Product desciption

Methods Of Microarray Data Analysis Ii Papers From Camda 01 1st Edition Simon M Lin by Simon M. Lin, Kimberly F. Johnson (eds.) 9780306475986, 9781402071119, 0306475987, 1402071116 instant download after payment.

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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