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Systems biology and bioinformatics : a computational approach / Kayvan Najarian ... [et al.]. — Boca Raton ; London : CRC Press, c2009. – (58.17115/S995) |
Contents
Contents
Preface xv
Acknowledgment xxi Authors xxiii
Chapter 1 Cell Biology 1
1.1 Introduction and Overview
1.2 An Introduction to Cell Structure
1.3 Proteins as Tools of the Cell
1.4 Genes: Directors of the Cell
1.5 Cell Cycle 12
1.6 Summary 13
1.7 Problems 13
Chapter 2 Bioassays 15
2.1 Introduction and Overview 15
2.2 Southern Blotting 15
2.3 Fluorescent In Situ Hybridization 15
2.4 Sanger (Dideoxy) Method 16
2.5 Polymerase Chain Reaction 16
2.6 Analyzing Protein Structure and Function 17
2.7 Studying Gene Expression and Function--DNA Microarrays 18
2.8 Summary 19
2.9 Problems 20
Chapter 3 Review of Some Computational Methods 21
3.1 Introduction and Overview 21
3.2 Introduction to Probability and Stochastic Processes Theories 21
3.3 Bayesian Theory 28
3.4 Test of Hypothesis 29
3.5 Expectation Maximization Method 31
3.6 Maximum Likelihood Theory 31
3.7 System Identification Theory 34
3.8 Summary 38
Problems 39
Chapter 4 Computational Structural Biology: Protein Structure Prediction 41
4.1 Introduction and Overview 41
4.2 Protein Structure Prediction Methods 42
4.3 Data Resources 46
4.4 Summary 50
4.5 Problems 50
References 50
Chapter 5 Computational Structural Biology: Protein Sequence Analysis 51
5.1 Introduction 51
5.2 Pairwise Sequence Matching 52
5.3 Multiple Sequence Alignment 55
5.4 Summary 56
5.5 Problems 57
Chapter 6 Genomics and Proteomics
6.1 Introduction and Overview 59
6.2 Genomics 59
6.3 Proteomics 61
6.4 Summary 63
6.5 Problems 64
Chapter 7 Methods for Identification of Differentially Expressed Genes or Proteins 65
7.1 Introduction and Overview 65
7.2 Why t Test Is Not Enough? 65
7.3 Mixture Model Method 66
7.4 Genes Involved in Leukemia: A Case Study 70
7.5 Summary 72
7.6 Problems 72
References 72
Chapter 8 Binary and Bayesian Networks as Static Models of Regulatory Pathways 73
8.1 Introduction and Overview
8.2 Binary Regulator Pathways
8.3 Bayesian Networks: Algorithm
8.4 Applications and Practical Considerations
8.5 Summary
8.6 Problems
Chapter 9 Metabolic Control Theory for Static Modeling of Metabolic Pathways 77
9.1 Introduction and Overview 77
9.2 Basic Ideas 77
9.3 Main Concepts in Metabolic Control Theory 79
9.4 Mason Method 83
9.5 Metabolic Control Model for Galactose Regulation Pathway: A Case Study 86
9.6 Summary 92
9.7 Problems 93
References 93
Chapter 10 System Identification and Control Theory for Dynamic Modeling of Biological Pathways 95
10.1 Introduction and Overview 95
10.2 Methodology 95
10.3 Modeling of Cell Cycle: A Case Study 102
10.4 Summary 106
10.5 Problems 106
References 107
Chapter 11 Gene Silencing for Systems Biology 109
11.1 Introduction and Overview
11.2 A Brief Review of RNA Interference， Small Interfering RNA， and Gene Silencing Mechanisms
11.3 Pathway Perturbation Using Gene Silencing
11.4 Summary
11.5 Problems References
Chapter 12 Simulation and Systems Biology 115
12.1 Introduction and Overview 115
12.2 What Is Simulation? 115
12.3 Challenges to Effective Simulation 117
12.4 Case Studies 120
12.5 Summary 129
12.6 Problems 129
References and Notes 129
Chapter 13 Software， Databases， and Other Resources for Systems Biology 131
13.1 Introduction and Overview
13.2 Databases
13.3 Scoring Matrix
13.4 Analysis Software 135
13.5 Bioinformatics in MATLAB 140
13.6 Summary 141
13.7 Problems 141
References 141
Chapter 14 Future Directions 143
14.1 Introduction and Overview 143
14.2 Single-Cell Microarray and Systems Biology 143
14.3 High-Throughput Protein Assays and Systems Biology 146
14.4 Integration of Molecular Data with Higher-Level Datasets 147
14.5 Identifying Genes Controlling Macrolevel Changes 150
14.6 Molecular-Level Image Systems and Systems Biology 153
14.7 Summary 155
14.8 Problems 155
References and Notes 156
Index 159
