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Data Management of Protein Interaction Networks

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Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e.g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and ...

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Data Management of Protein Interaction Networks

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Overview

Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e.g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and storing PPI data. It also describes main algorithms and tools for the analysis, comparison and knowledge extraction from PINs. Moreover, some case studies and applications of PINs are also discussed.

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Editorial Reviews

From the Publisher
“The material is suitable for researchers, practitioners, and graduate students in bioinformatics, molecular biology, biomedicine, and biotechnology.” (Book News, 1 April 2012)
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Product Details

  • ISBN-13: 9780470770405
  • Publisher: Wiley
  • Publication date: 11/22/2011
  • Series: Wiley Series in Bioinformatics Series , #17
  • Edition number: 1
  • Pages: 216
  • Product dimensions: 6.90 (w) x 9.90 (h) x 1.40 (d)

Meet the Author

MARIO CANNATARO, PhD, is Associate Professor of Computer Engineering at the Magna Græcia University of Catanzaro. His research explores bioinformatics, computational proteomics and genomics, medical informatics, grid and parallel computing, and adaptive web systems. Dr. Cannataro has published three books and more than 150 papers in international journals and conference proceedings.

PIETRO HIRAM GUZZI, PhD, is Assistant Professor of Computer Engineering at the Magna Græcia University of Catanzaro. His research focuses on the analysis of protein interaction networks and the use of biological knowledge encoded in ontologies for modeling, querying, and analyzing protein interaction networks.

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Table of Contents

List Of Figures xiii

List Of Tables xix

Foreword xxi

Preface xxiii

Acknowledgments xxix

Introduction xxxi

Acronyms xxxiii

1 Interactomics 1

1.1 Interactomics and Omics Sciences 1

1.2 Genomics and Proteomics 4

1.3 Representation and Management of Protein Interaction Data 5

1.4 Analysis of Protein Interaction Networks 5

1.5 Visualization of Protein Interaction Networks 6

1.6 Models for Biological Networks 7

1.7 Flow of Information in Interactomics 8

1.8 Applications of Interactomics in Biology and Medicine 10

1.9 Summary 11

2 Technologies For Discovering Protein Interactions 13

2.1 Introduction 13

2.2 Techniques Investigating Physical Interactions 14

2.3 Technologies Investigating Kinetic Dynamics 17

2.4 Summary 18

3 Graph Theory And Applications 21

3.1 Introduction 21

3.2 Graph Data Structures 22

3.3 tGraph-Based Problems and Algorithms 28

3.4 Summary 31

Protein-To-Protein Interaction Data 33

4.1 Introduction 33

4.2 HUPO PSI-MI 34

4.3 Summary 41

5 Protein-To-Protein Interaction Databases 43

5.1 Introduction 43

5.2 Databases of Experimentally Determined Interactions 45

5.3 Databases of Predicted Interactions 55

5.4 Metadatabases: Integration of PPI Databases 62

5.5 Summary 70

6 Models For Protein Interaction Networks 71

6.1 Introduction 71

6.2 Random Graph Model 72

6.3 Scale-Free Model 73

6.4 Geometric Random Graph Model 73

6.5 Stickiness Index (STICKY) Model 74

6.6 Degree-Weighted Model 74

6.7 Network Scoring Models 75

6.8 Summary 76

7 Algorithms Analyzing Features Of Protein Interaction Networks 79

7.1 Introduction 79

7.2 Analysis of Protein Interaction Networks through Centrality Measures 80

7.3 Extraction of Network Motifs 81

7.4 Individuation of Protein Complexes 88

7.5 Summary 99

8 Algorithms Comparing Protein Interaction Networks 101

8.1 Introduction 101

8.2 Local Alignment Algorithms 104

8.3 Global Alignment Algorithms 109

8.4 Summary 111

9 Ontology-Based Analysis Of Protein Interaction Networks 113

9.1 Definition of Ontology 113

9.2 Languages for Modeling Ontologies 115

9.3 Biomedical Ontologies 116

9.4 Ontology-Based Analysis of Protein Interaction Data 117

9.5 Semantic Similarity Measures of Proteins 120

9.6 The Gene Ontology Annotation Database (GOA) 122

9.7 FussiMeg and ProteinOn 123

9.8 Summary 123

10 Visualization Of Protein Interaction Networks 125

10.1 Introduction 125

10.2 Cytoscape 126

10.3 CytoMCL 127

10.4 NAViGaTOR 128

10.5 BioLayout Express 130

10.6 Medusa 130

10.7 ProViz 131

10.8 Ondex 132

10.9 PIVOT 132

10.10 Pajek 133

10.11 Graphviz 134

10.12 GraphCrunch 134

10.13 VisANT 135

10.14 PIANA 136

10.15 Osprey 136

10.16 cPATH 137

10.17 PATIKA 138

10.18 Summary 139

11 Case Studies In Biology And Bioinformatics 141

11.1 Analysis of an Interaction Network from Proteomic Data 141

11.2 Experimental Comparison of Two Interaction Networks 143

11.3 Ontology-Based Management of PIN (OntoPIN) 145

11.4 Ontology-Based Prediction of Protein Complexes 149

12 Future Trends 151

References 157

Index 177

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