A practical approach to microarray data analysis / edited by Daniel P. Berrar, Werner Dubitzky, Martin Granzow.

Format:

Book

Contributor:

Berrar, Daniel P., 1972-

Dubitzky, Werner, 1958-

Granzow, Martin, 1970-

Language:

English

Subjects (All):

DNA microarrays.

Oligonucleotide Array Sequence Analysis--methods.

Medical Subjects:

Oligonucleotide Array Sequence Analysis--methods.

Physical Description:

xv, 368 pages : illustrations ; 25 cm

Place of Publication:

Boston, MA : Kluwer Academic Publishers, [2003]

Summary:

A Practical Approach to Microarray Data Analysis is for all life scientists, statisticians, computer experts, technology developers, managers, and other professionals tasked with developing, deploying, and using microarray technology including the necessary computational infrastructure and analytical tools. The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduateor graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.

Contents:

2 Data Pre-Processing Issues in Microarray Analysis / Nicholas A. Tinker, Laurian S. Robert, Gail Butler, Linda J. Harris 47

3 Missing Value Estimation / Olga G. Troyanskaya, David Botstein, Russ B. Altman 65

4 Normalization / Norman Morrison, David C. Hoyle 76

5 Singular Value Decomposition and Principal Component Analysis / Michael E. Wall, Andreas Rechtsteiner, Luis M. Rocha 91

6 Feature Selection in Microarray Analysis / Eric P. Xing 110

7 Introduction to Classification in Microarray Experiments / Sandrine Dudoit, Jane Fridlyand 132

8 Bayesian Network Classifiers for Gene Expression Analysis / Byoung-Tak Zhang, Kyu-Baek Hwang 150

9 Classifying Microarray Data Using Support Vector Machines / Sayan Mukherjee 166

10 Weighted Flexible Compound Covariate Method for Classifying Microarray Data / Yu Shyr, KyungMann Kim 186

11 Classification of Expression Patterns Using Artificial Neural Networks / Markus Ringner, Patrik Eden, Peter Johansson 201

12 Gene Selection and Sample Classification Using a Genetic Algorithm and k-Nearest Neighbor Method / Leping Li, Clarice R. Weinberg 216

13 Clustering Genomic Expression Data: Design and Evaluation Principles / Francisco Azuaje, Nadia Bolshakova 230

14 Clustering or Automatic Class Discovery: Hierarchical Methods / Derek C. Stanford, Douglas B. Clarkson, Antje Hoering 246

15 Discovering Genomic Expression Patterns with Self-Organizing Neural Networks / Francisco Azuaje 261

16 Clustering or Automatic Class Discovery: non-hierarchical, non-SOM / Ka Yee Yeung 274

17 Correlation and Association Analysis / Simon M. Lin, Kimberly F. Johnson 289

18 Global Functional Profiling of Gene Expression Data / Sorin Draghici, Stephen A. Krawetz 306

19 Microarray Software Review / Yuk Fai Leung, Dennis Shun Chiu Lam, Chi Pui Pang 326

20 Microrray Analysis as a Process / Susan Jensen 345.

Notes:

Includes bibliographical references and index.

ISBN:

1402072600

OCLC:

50519150