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A Practical Approach to Microarray Data Analysis

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Cover of 'A Practical Approach to Microarray Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Microarray Data Analysis
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    Chapter 2 Data Pre-Processing Issues in Microarray Analysis
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    Chapter 3 Missing Value Estimation
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    Chapter 4 Normalization
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    Chapter 5 Singular Value Decomposition and Principal Component Analysis
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    Chapter 6 Feature Selection in Microarray Analysis
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    Chapter 7 Introduction to Classification in Microarray Experiments
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    Chapter 8 Bayesian Network Classifiers for Gene Expression Analysis
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    Chapter 9 Classifying Microarray Data Using Support Vector Machines
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    Chapter 10 Weighted Flexible Compound Covariate Method for Classifying Microarray Data
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    Chapter 11 Classification of Expression Patterns Using Artificial Neural Networks
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    Chapter 12 Gene Selection and Sample Classification Using a Genetic Algorithm and k-Nearest Neighbor Method
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    Chapter 13 Clustering Genomic Expression Data: Design and Evaluation Principles
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    Chapter 14 Clustering or Automatic Class Discovery: Hierarchical Methods
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    Chapter 15 Discovering Genomic Expression Patterns with Self-Organizing Neural Networks
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    Chapter 16 Clustering or Automatic Class Discovery: Non-Hierarchical, non-SOM
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    Chapter 17 Correlation and Association Analysis
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    Chapter 18 Global Functional Profiling of Gene Expression Data
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    Chapter 19 Microarray Software Review
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    Chapter 20 Microarray Analysis as a Process
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Title
A Practical Approach to Microarray Data Analysis
Published by
Springer US, May 2007
DOI 10.1007/b101875
ISBNs
978-1-4020-7260-4, 978-0-306-47815-4
Editors

Berrar, Daniel P., Dubitzky, Werner, Granzow, Martin

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 25%
Student > Ph. D. Student 6 15%
Student > Bachelor 5 13%
Student > Postgraduate 3 8%
Student > Doctoral Student 2 5%
Other 6 15%
Unknown 8 20%
Readers by discipline Count As %
Engineering 10 25%
Computer Science 7 18%
Agricultural and Biological Sciences 5 13%
Chemistry 4 10%
Mathematics 3 8%
Other 2 5%
Unknown 9 23%

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