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Data Analysis and Visualization in Genomics and Proteomics Hardback - 2005 - 1st Edition
by Azuaje, Francisco (Editor)/ Dopazo, Joaquin (Editor)
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- Hardback
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Details
- Title Data Analysis and Visualization in Genomics and Proteomics
- Author Azuaje, Francisco (Editor)/ Dopazo, Joaquin (Editor)
- Binding Hardback
- Edition number 1st
- Edition 1
- Condition New
- Pages 284
- Volumes 1
- Language ENG
- Publisher John Wiley & Sons Inc
- Publication date 2005
- Illustrated Yes
- Features Bibliography, Illustrated, Index, Table of Contents
- Bookseller's Inventory # x-0470094397
- ISBN 9780470094396 / 0470094397
- Weight 1.51 lbs (0.68 kg)
- Dimensions 9.96 x 6.62 x 0.86 in (25.30 x 16.81 x 2.18 cm)
- Category Medical / Nursing
- Library of Congress subjects Data mining, Proteomics - Data processing
- Library of Congress Catalogue Number 2005006838
- Dewey Decimal Code 572.86
- Quantity available 2
About Revaluation Books Devon, United Kingdom
Biblio member since 2020
General bookseller of both fiction and non-fiction.
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From the publisher
From the rear cover
This book provides scientists and students with the basis for the development of integrative computational approaches to analysing biological data on a systemic scale. It emphasises the processing of multiple data and knowledge resources, and the combination of different prediction models and systems. It covers different data analysis and visualisation techniques for studying the roles of genes and proteins at a systems level. A fairly broad definition for the areas of genomics and proteomics is adopted, which also encompasses a wider spectrum of 'omic' approaches required to understand the functions of genes and their products.
From a bioinformatics point of view, the book illustrates: how data analysis techniques can facilitate more comprehensive, user-friendly data visualisation tasks; how data visualisation methods may make data analysis a more meaningful and biologically relevant process; and how to approach the overabundance of data in genomic studies, in which spurious associations often occur, with the proper statistical tools. The book describes how this synergy may support integrative approaches to functional genomics.
The book will be of interest to all bioinformaticians, from students to researchers, as well as to many scientists working in genomics, proteomics, systems biology and related areas.
