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Advanced analysis of gene expression microarray data / Aidong Zhang. — New Jersey : World Scientific, 2006.—(58.215/Z63) |
Contents
Contents
Preface
1. Introduction
1.1 The Microarray: Key to Functional Genomics and Systems Biology
1.2 Applications of Microarray
1.3 Framework of Microarray Data Analysis
1.4 Summary
2. Basic Concepts of Molecular Biology
2.1 Introduction.
2.2 Cells
2.3 Proteins
2.4 Nucleic Acids
2.5 Central Dogma of Molecular Biology
2.6 Genotype and Phenotype
2.7 Summary
3. Overview of Microarray Experiments
3.1 Introduction
3.2 Microarray Chip Manufacture
3.3 Steps of Microarray Experiments
3.4 Image Processing
3.5 Microarray Data Cleaning and Preprocessing
3.6 Data Normalization
3.7 Summary
4. Analysis of Differentially-Expressed Genes
4.1 Introduction
4.2 Basic Concepts in Statistics
4.3 Fold Change Methods
4.4 Parametric Tests
4.5 Non-Parametric Tests
4.6 Multiple Testing
4.7 ANOVA: Analysis of Variance
4.8 Summary
5. Gene-Based Analysis
5.1 Introduction
5.2 Proximity Measurement for Gene Expression Data
5.3 Partition-Based Approaches
5.4 Hierarchical Approaches
5.5 Density-Based Approaches
5.6 GPX: Gene Pattern eXplorer
5.7 Cluster Validation
5.8 Summary
6. Sample-Based AnMysis
6.1 Introduction
6.2 Selection of Informative Genes
6.3 Class Prediction
6.4 Class Discovery
6.5 Classification Validation
6.6 Summary
7. Pattern-Based Analysis
7.1 Introduction
7.2 Mining Association Rules
7.3 Mining Pattern-Based Clusters in Microarray Data
7.4 Mining Gene-Sample-Time Microarray Data
7.5 Summary
8. Visualization of Microarray Data
8.1 Introduction
8.2 Single-Array Visualization
8.3 Multi-Array Visualization
8.4 VizStruct
8.5 Summary
9. New Trends in Mining Gene Expression Microarray Data
9.1 Introduction
9.2 Meta-Analysis of Microarray Data
9.3 Semi-Supervised Clustering
9.4 Integration of Gene Expression Data with Other Data
9.5 Summary
10. Conclusion
Bibliography
Index
