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Analysis of Microarray Gene Expression Data

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Cover of 'Analysis of Microarray Gene Expression Data'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 DNA, RNA, Protein, and Gene Expression
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    Chapter 3 Microarray Technology
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    Chapter 4 Inherent Variability in Microarray Data
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    Chapter 5 Background Noise
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    Chapter 6 Transformation and Normalization
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    Chapter 7 Missing Values in Microarray Data
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    Chapter 8 Saturated Intensity Readings in Microarray Data
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    Chapter 9 Experimental Design
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    Chapter 10 Anova Models for Michrorray Data
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    Chapter 11 Multiple Testing in Microarray Studies
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    Chapter 12 Permutation Tests in Microarray Data
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    Chapter 13 Bayesian Methods for Microarray Data
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    Chapter 14 Power and Sample Size Considerations at the Planning Stage
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    Chapter 15 Cluster Analysis
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    Chapter 16 Principal Components and Singular Value Decomposition
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    Chapter 17 Self-organizing Maps
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    Chapter 18 Discrimination and Classification
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    Chapter 19 Artificial Neural Networks
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    Chapter 20 Support Vector Machines
Attention for Chapter 18: Discrimination and Classification
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