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Complexity in Chemistry, Biology, and Ecology / edited by Danail Bonchev and Dennis H. Rouvray. —New York : Springer, 2005.—(53.821/C737) |
Contents
Contents
1. ON THE COMPLEXITY OF FULLERENES AND NANOTUBES 1
1. Introduction 1
2. On the Complexity of the Complexity Concept 3
3. Complexity and Branching 4
4. Complexity of Smaller Molecules 7
5. Augmented Valence as a Complexity Index 16
6. Complexity of Smaller Fullerenes 20
7. Comparison of Local Atomic Environments 25
8. The Role of Symmetry 29
9. Concluding Remarks on the Complexity of Fullerenes 34
10. On the Complexity of Carbon Nanotubes 36
Acknowledgement 43
References 44
2. COMPLEXITY AND SELF-ORGANIZATION IN BIOLOGICAL DEVELOPMENT AND EVOLUTION 49
1. Introduction: Complex Chemical Systems in Biological Development and Evolution 49
2. Dynamic， Multistability and Cell Differentiation 51
3. Biochemical Oscillations and Segmentation 65
4. Reaction-Diffusion Mechanisms and Embryonic Pattern Formation 70
5. Evolution of Developmental Mechanisms 76
6. Conclusions 89
References 91
3. THE CIRCLE THAT NEVER ENDS: CAN COMPLEXITY BE MADE SIMPLE? 97
1. Introduction: The Nature of the Problem and Why it Has No Clear Solution 97
2. An Introduction to Relational Systems Theory 103
3. The Structure of Network Thermodynamics as Formalism 118
4. Simulation of Non-Linear Networks on Spice 133
5. Relational Networks and Beyond 138
References 148
4. GRAPHS AS MODELS OF LARGE-SCALE BIOCHEMICAL ORGANIZATION 155
1. Introduction 155
2. Basic Properties of Random Graphs 157
3. Protein Structure and Contact Graphs 164
4. Protein Interaction Networks 169
5. Gene Networks 180
6. Overview 187
Acknowledgements 188
References 188
5. QUANTITATIVE MEASURES OF NETWORK COMPLEXITY 191
1. Some History 191
2. Networks as Graphs 193
3. How to Measure Network Complexity 202
4. Combined Complexity Measures Based on the Graph Adjacency and Distance 213
5. Vertex Accessibility and Complexity of Directed Graphs 218
6. Complexity Estimates of Biological and Ecological Networks 221
7. Overview 230
Acknowledgement 232
References 232
6. CELLULAR AUTOMATA MODELS OF COMPLEX BIOCHEMICAL SYSTEMS 237
1. Reality， Systems， and Models 237
2. General Principles of Complexity 248
3. Modeling Emergence in Complex Biosystems 257
4. Examples of Cellular Automata Models 274
5. General Summary 297
References 298
7. THE COMPLEX NATURE OF ECODYNAMICS 303
1. Introduction 303
2. Measuring The Effects of Incorporated Constraints 306
3. Ecosystems and Contingency 307
4. Autocatalysis and Non-Mechanical Behavior 311
5. Causality Reconsidered 316
6. Quantifying Constraint in Ecosystems 318
7. New Constraints to Help Focus a New Perspective 324
Acknowledgements 327
References 327
NAME INDEX 331
