Networks in Cell Biology

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The science of complex biological networks is transforming research in areas ranging from evolutionary biology to medicine. This is the first book on the subject, providing a comprehensive introduction to complex network science and its biological applications. With contributions from key leaders in both network theory and modern cell biology, this book discusses the network science that is increasingly foundational for systems biology and the quantitative understanding of living systems. It surveys studies in the quantitative structure and dynamics of genetic regulatory networks, molecular networks underlying cellular metabolism, and other fundamental biological processes. The book balances empirical studies and theory to give a unified overview of this interdisciplinary science. It is a key introductory text for graduate students and researchers in physics, biology and biochemistry, and presents ideas and techniques from fields outside the reader's own area of specialization.

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Editorial Reviews

From the Publisher
“Network science has experienced a spectacular explosion in the past decade, influencing a wide range of fields, from computer science to sociology. Yet, nowhere is the impact of the new theoretical framework as promising as it is in cell biology - many of the difficult open questions cannot be understood without a network based approach. Modelling Cell Biology with Networks offers an excellent introduction to this frontier, at the same time capturing the current state of research. With contributions from the best in the field, it is a valuable addition to the shelf of anyone interested in this exciting area.”
Albert-László Barabási, Center for Complex Network Research Northeastern University and Department of Medicine, Harvard Medical School

“This book describes the state of the art in understanding cellular networks through contributions by leaders in modern cell biology and network theory. It is clearly organized and exhibits an excellent balance between empirical studies and theory. The biological underpinnings are explained clearly and comprehensively, and the appendices give a great primer to the key mathematical concepts necessary for network analysis and modeling. This book will be of great use as a course textbook or for self-study.”
Reka Albert, Pennsylvania State University

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Product Details

  • ISBN-13: 9780521882736
  • Publisher: Cambridge University Press
  • Publication date: 6/30/2010
  • Pages: 280
  • Product dimensions: 6.80 (w) x 9.80 (h) x 0.70 (d)

Meet the Author

Mark Buchanan is a physicist and independent author. He writes a monthly column for the journal Nature Physics.

Guido Caldarelli is Associate Professor in the Centre for Statistical Mechanics, University of Rome 'Sapienza', Italy.

Paolo De Los Rios is a Professor in the Laboratory of Statistical Biophysics, Institute of Theoretical Physics, École Polytechnique Fédérale de Lausanne (EPFL).

Francesco Rao researches in the Laboratoire de Chimie Biophysique, University of Strasbourg.

Michele Vendruscolo is a Reader in Theoretical Chemical Biology at the Department of Chemistry, University of Cambridge.

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Table of Contents

List of contributors viii

Introduction M. Buchanan G. Caldarelli P. De Los Rios F. Rao M. Vendruscolo 1

1 Network views of the cell Paolo De Los Rios Michele Vendruscolo 4

1.1 The network hypothesis 4

1.2 The central dogma and gene regulatory networks 5

1.3 Protein-protein interaction networks 7

1.4 Metabolic networks 9

1.5 Signaling networks 11

1.6 Networked networks and cell functionality 12

1.7 Concluding remarks 13

2 Transcriptional regulatory networks Sarath Chandra Janga M. Madan Babu 14

2.1 Introduction 14

2.2 Transcriptional regulation in prokaryotes and eukaryotes 19

2.3 Structure of transcriptional regulatory networks 20

2.4 Evolution of transcriptional regulatory networks 25

2.5 Dynamics of transcriptional regulatory networks 29

2.6 Conclusions 34

3 Transcription factors and gene regulatory networks Matteo Brilli Elisa Calistri Pietro Lió 36

3.1 Introduction 36

3.2 Promoters' complexity/eukaryotic gene promoters 37

3.3 Transcription factors 41

3.4 Bioinformatics of regulatory networks 46

4 Experimental methods for protein interaction identification Peter Uetz Björn Titz Seesandra V. Rajagopala Gerard Cagney 53

4.1 Introduction 53

4.2 Protein complementation techniques 57

4.3 Affinity purification methods 62

4.4 Protein complex purification and mass spectrometry 65

4.5 Protein and peptide chips 73

4.6 Other methods for interaction detection and functional analysis 74

4.7 Quality of large-scale interaction data 75

4.8 Comparison of methods 77

4.9 Conclusions 80

5 Modeling protein interaction networks Francesco Rao 83

5.1 Introduction 83

5.2 Scaling laws and network topology 85

5.3 Predicting protein interactions 87

5.4 Towards models at an atomic level of resolution 88

5.5 Concluding remarks 90

6 Dynamics and evolution of metabolic networks Daniel Segrè 93

6.1 Introduction 93

6.2 Cellular metabolism and its regulation 93

6.3 Metabolism across disciplines 96

6.4 Dynamics of a metabolic system 98

6.5 Stoichiometric analysis 100

6.6 Constraint-based modeling: feasible states and optimality 103

6.7 Predicting genetic perturbations 108

6.8 Double perturbations and epistatic interactions 109

6.9 The ancient history of metabolism: from cell-scale to biosphere-scale 112

6.10 Conclusions 116

7 Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan 117

7.1 Introduction 117

7.2 Modularity and hubs in biological networks 119

7.3 Scaling of the clustering coefficient: a signature of hierarchy 121

7.4 Method for finding network modules 123

7.5 A case study: the E. coli metabolic network 126

7.6 Hierarchy, fractality and the small world of networks 131

7.7 Conclusions 134

8 Signalling networks Gian Paolo Rossini 135

8.1 Introduction 135

8.2 Chemical signalling: many pathways following a few general themes 136

8.3 Cross-talks among signal transduction pathways 159

8.4 Signalling networks, system organization and modelling 166

8.5 Conclusions and outlook 169

Appendix A Complex networks: from local to global properties D. Garlaschelli G. Caldarelli 170

Appendix B Modelling the local structure of networks D. Garlaschelli G. Caldarelli 188

Appendix C Higher-order topological properties S. Ahnert T. Fink G. Caldarelli 210

Appendix D Elementary mathematical concepts A. Gabrielli G. Caldarelli 219

References 235

Index 269

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