Complexity in Chemistry, Biology, and Ecology (eBook)
XX, 348 Seiten
Springer US (Verlag)
978-0-387-25871-3 (ISBN)
Internationally established experts present the inspiring new science of complexity, which discovers new general laws covering wide range of science areas.
The book offers a broader view on complexity based on the expertise of the related areas of chemistry, biochemistry, biology, ecology, and physics.
Contains methodologies for assessing the complexity of systems that can be directly applied to proteomics and genomics, and network analysis in biology, medicine, and ecology.
As we were at pains to point out in the companion volume to this mo- graph, entitled Complexity in Chemistry: Introduction and Fundamentals, complexity is to be encountered just about everywhere. All that is needed forustoseeitisasuitablytrainedeyeanditthenappearsalmostmagically in all manner of guises. Because of its ubiquity, complexity has been and currentlystillisbeingde?nedinanumberofdifferentways. Someofthese de?nitions have led us to major and powerful new insights. Thus, even in the present monograph, the important distinction is drawn between the - terpretations of the concepts of complexity and complication and this is shown to have a signi?cant bearing on how systems are modeled. Having said this, however, we should not fail to mention that the broad consensus that now gained acceptance is that all of the de?nitions of complexity are in the last analysis to be understood in essentially intuitive terms. Such de?nitions will therefore always have a certain degree of fuzziness as- ciated with them. But this latter desideratum should in no way be viewed as diminishing the great usefulness of the concept in any of the many scienti?c disciplines to which it can be applied. In the chapters that are included in this monograph the fact that differing concepts of complexity can be utilized in a variety of disciplines is made explicit. The speci?c d- ciplines that we embrace herein are chemistry, biochemistry, biology, and ecology. Chapter 1, "e;On the Complexity of Fullerenes and Nanotubes,"e; is wr- ten by an international team of scientists led by Milan Randic.
CONTRIBUTORS 6
PREFACE 8
CONTENTS 16
ON THE COMPLEXITY OF FULLERENES AND NANOTUBES 22
1. Introduction 22
2. On the Complexity of the Complexity Concept 24
3. Complexity and Branching 25
4. Complexity of Smaller Molecules 28
5. Augmented Valence as a Complexity Index 37
6. Complexity of Smaller Fullerenes 41
7. Comparison of Local Atomic Environments 46
8. The Role of Symmetry 50
9. Concluding Remarks on the Complexity of Fullerenes 55
10. On the Complexity of Carbon Nanotubes 57
COMPLEXITY AND SELF-ORGANIZATION IN BIOLOGICAL DEVELOPMENT AND EVOLUTION 70
1. Introduction: Complex Chemical Systems in Biological Development and Evolution 70
2. Dynamic Multistability and Cell Differentiation 72
3. Biochemical Oscillations and Segmentation 86
4. Reaction-Diffusion Mechanisms and Embryonic Pattern Formation 91
5. Evolution of Developmental Mechanisms 97
6. Conclusions 110
THE CIRCLE THAT NEVER ENDS: CAN COMPLEXITY BE MADE SIMPLE? 117
1. Introduction: The Nature of the Problem and Why it Has No Clear Solution 117
2. An Introduction to Relational Systems Theory 123
3. The Structure of Network Thermodynamics as Formalism 138
4. Simulation of Non-Linear Networks on Spice 153
5. Relational Networks and Beyond 158
GRAPHS AS MODELS OF LARGE-SCALE BIOCHEMICAL ORGANIZATION 174
1. Introduction 174
2. Basic Properties of Random Graphs 176
3. Protein Structure and Contact Graphs 183
4. Protein Interaction Networks 188
5. Gene Networks 199
6. Overview 206
QUANTITATIVE MEASURES OF NETWORK COMPLEXITY 209
1. Some History 209
2. Networks as Graphs 211
3. How to Measure Network Complexity 220
4. Combined Complexity Measures Based on the Graph Adjacency and Distance 231
5. Vertex Accessibility and Complexity of Directed Graphs 236
6. Complexity Estimates of Biological and Ecological Networks 239
7. Overview 248
CELLULAR AUTOMATA MODELS OF COMPLEX BIOCHEMICAL SYSTEMS 254
1. Reality, Systems, and Models 254
2. General Principles of Complexity 265
3. Modeling Emergence in Complex Biosystems 274
4. Examples of Cellular Automata Models 291
5. General Summary 314
THE COMPLEX NATURE OF ECODYNAMICS 319
1. Introduction 319
2. Measuring the Effects of Incorporated Constraints 322
3. Ecosystems and Contingency 323
4. Autocatalysis and Non-Mechanical Behavior 327
5. Causality Reconsidered 332
6. Quantifying Constraint in Ecosystems 334
7. New Constraints to Help Focus a New Perspective 340
AUTHOR INDEX 346
SUBJECT INDEX 352
Erscheint lt. Verlag | 3.5.2007 |
---|---|
Reihe/Serie | Mathematical and Computational Chemistry | Mathematical and Computational Chemistry |
Zusatzinfo | XX, 348 p. |
Verlagsort | New York |
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
Naturwissenschaften ► Biologie | |
Naturwissenschaften ► Chemie ► Physikalische Chemie | |
Technik | |
Schlagworte | biochemistry • Biology • Chemistry • Complexity • Development • Ecology • ecosystem • Ecosystems • Evolution • Genetic Engineering • genomics • Information • Information Theory • nanotechnology • Proteomics • Topology |
ISBN-10 | 0-387-25871-X / 038725871X |
ISBN-13 | 978-0-387-25871-3 / 9780387258713 |
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