Introduction to Systems Biology (eBook)

Preface 5
Contents 7
Contributors 11
Part I Introduction 18
Scientific Challenges in Systems Biology 19
1. Introduction 19
2. Robustness as a Fundamental Organizational Principle 21
3. Intrinsic Nature of Robust Systems 23
4. Technology Platforms in Systems Biology 24
Bringing Genomes to Life: The Use of Genome-Scale In Silico Models 30
1. Introduction 30
2. Properties of Biological Networks 33
3. Reconstruction of Metabolic Networks 34
4. Mathematical Characterization of Network Capabilities 39
5. Two Sample Studies 45
6. Further Levels of Annotation 49
7. Future Directions 50
From Gene Expression to Metabolic Fluxes 53
1. Introduction 53
2. Engineering a Cell: A Systems Approach 56
3. Omics Quantification 65
4. Models for Metabolic Engineering in the Systems Biology Era 69
5. Conclusions 75
Part II Experimental Techniques for Systems Biology 83
Handling and Interpreting Gene Groups 85
1. Introduction 85
2. Accession Numbers 86
3. Handling and Comparing Gene Groups 88
4. Functional Interpretation of Gene Groups 90
5. Retrieval and Analysis of Sequences 94
6. Conclusions 96
The Dynamic Transcriptome of Mice 101
1. Introduction 101
2. Mouse Encyclopedia Project 102
3. Technology Used for the Mouse cDNA Encyclopedia 102
4. FANTOM 110
5. Future Prospects 116
6. Conclusions 118
Dissecting Transcriptional Control Networks 122
1. Introduction 122
2. Information Theoretic Weight Matrix and the Problem of Thresholds 124
3. Combining Heterogeneous Data: Going Beyond Sequence 130
4. Combining Phylogenetic Footprinting and Motif Search 132
5. Conclusion 135
Reconstruction and Structural Analysis of Metabolic and Regulatory Networks 140
1. Introduction 140
2. Methods for Reconstruction of Metabolic Networks and Regulatory Networks 141
3. Graph Representation of Biological Networks 147
4. Structural Analysis of Biological Networks 150
5. Conclusions 159
Cross-Species Comparison Using Expression Data 163
1. Introduction 163
2. Chapter Outline 164
3. Information Required to Compare Expression Between Species 164
4. Available Tools and Methodologies 168
5. Using Expression Data Provides New Insight into Cross- Species Comparisons 170
6. Conclusion 173
Methods for Protein–Protein Interaction Analysis 176
1. MS-Based Approaches for PPIs 176
2. Two-Hybrid Approaches for Protein Interactions 187
3. Conclusion 195
Genome-Scale Assessment of Phenotypic Changes During Adaptive Evolution 199
1. Introduction to Adaptive Evolution 199
2. Adaptive Evolution and Systems Biology 200
3. Genotype to Phenotype in Adaptive Evolution 202
4. Genome-Scale Phenotype Assessment 204
5. Summary 210
Location Proteomics 212
1. Introduction 212
2. Approaches to Determining Subcellular Location 214
3. Automated Analysis of Subcellular Patterns 216
4. Systematic Comparison and Clustering 223
5. Models of Subcellular Patterns 225
Part III Theoretical and Modeling Techniques 231
Reconstructing Transcriptional Networks Using Gene Expression Profiling and Bayesian State- Space Models 233
1. Introduction 234
2. Modeling Time Series with SSMs 236
3. Results 243
4. Conclusions 254
Modeling Spatiotemporal Dynamics of Multicellular Signaling 258
1. Introduction 258
2. Methods 260
3. Applications 265
4. Discussion 272
Kinetics of Dimension-Restricted Conditions 277
1. In Vivo–Oriented Modeling 277
2. DRRK 279
3. Planning the Experiments for the Model 285
4. Calculation Cost: Another Benefit of the DRRK Model 292
5. Concluding Remarks 292
Appendix A: Steady-State Conditions and Reaction Order Estimation 293
Appendix B: The Relation Between Rate Constant and Diffusion Coefficient 294
Mechanisms Generating Ultrasensitivity, Bistability, and Oscillations in Signal Transduction 298
1. Introduction 298
2. Quantification of Ultrasensitivity 300
3. Mechanisms 302
4. Effect of Feedbacks on Ultrasensitive Cascades 307
5. Discussion 312
Employing Systems Biology to Quantify Receptor Tyrosine Kinase Signaling in Time and Space 316
1. Introduction 316
2. Challenges of Mechanistic Modeling 318
3. Complex Temporal Dynamics of Signaling Networks 321
4. Spatial Dimension of Cell Signaling 322
5. Facilitated Mechanisms for Intracellular Signal Propagation 327
6. Outlook 329
Dynamic Instabilities Within Living Neutrophils 335
1. Introduction 335
2. Computational Biology of Neutrophil Oscillators 337
3. Biomechanisms 341
4. Conclusions 347
Efficiency, Robustness, and Stochasticity of Gene Regulatory Networks in Systems Biology: l Switch as a Working Example 352
1. Introduction 352
2. Phage l Genetic Switch 355
3. Towards Quantitative Modeling 358
4. Stochastic Dynamical Modeling 364
5. Quantitative Comparison Between Theory and Experiment 368
6. Perspective on Mathematical Modeling 377
7. Third Age of Phage 380
Applications, Representation, and Management of Signaling Pathway Information: Introduction to the SigPath Project 388
1. Introduction 388
2. Signaling Pathways 389
3. Knowledge Representation and Modeling 390
4. Applications of Signaling Pathway Information 391
5. Representing Signaling Pathways to Support Biomedical Research 395
6. The SigPath Project 399
Part IV Methods and Software Platforms for Systems Biology 409
SBML Models and MathSBML 411
1. Motivation 411
2. The Evolution of SBML 412
3. SBML Level 2 Models 414
4. Proposed Modifications to SBML 422
5. Resources at http://sbml.org 424
6. BioModels Database 427
7. Managing SBML with MathSBML 428
CellDesigner: A Graphical Biological Network Editor and Workbench Interfacing Simulator 438
1. Introduction 438
2. Features of CellDesigner 439
3. How Does it Work? 446
4. What Distinguishes CellDesigner’s Technology from Others Currently Available? 447
5. Future Work 448
6. Conclusion 449
DBRF-MEGN Method: An Algorithm for Inferring Gene Regulatory Networks from Large- Scale Gene Expression Profiles 451
1. Introduction 451
2. Algorithm 452
3. Application 456
4. Software 459
5. Perspectives 461
Systematic Determination of Biological Network Topology: Nonintegral Connectivity Method ( NICM) 465
1. Introduction 465
2. Methods 466
3. Analysis of Yeast Glycolytic Network 479
4. Conclusion 480
Appendix 1 483
Appendix 2 484
Storing, Searching, and Disseminating Experimental Proteomics Data 488
1. Introduction 488
2. Previous Work 490
3. Modeling Proteomics Data 491
4. Capturing and Disseminating 494
5. Conclusions and Future Perspectives 498
Representing and Analyzing Biochemical Networks Using BioMaze 500
1. General Introduction 500
2. Data Models for Representing Biochemical Networks 502
3. Data Models for Analyzing Biochemical Networks 509
4. Analysis of Biochemical Networks 513
5. Implementation Aspects 516
6. Concluding Remarks 518
Appendices 525
Software, Databases, and Websites for Systems Biology 527
Glossary 533
Index 543