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Analysis of Biological Networks
John Wiley and Sons Ltd, April 2008, Pages: 368
Foreword
Preface
Contributors
PART I INTRODUCTION
1 Networks in Biology
Bjo¨rn H. Junker
1.1 Introduction
1.2 Biology 101
1.2.1 Biochemistry and Molecular Biology
1.2.2 Cell Biology
1.2.3 Ecology and Evolution
1.3 Systems Biology
1.4 Properties of Biological Networks
1.4.1 Networks on a Microscopic Scale
1.4.2 Networks on a Macroscopic Scale
1.4.3 Other Biological Networks
1.5 Summary
1.6 Exercises
References
2 Graph Theory
Falk Schreiber
2.1 Introduction
2.2 Basic Notation
2.2.1 Sets
2.2.2 Graphs
2.2.3 Graph Attributes
2.3 Special Graphs
2.3.1 Undirected, Directed, Mixed, and Multigraphs
2.3.2 Hypergraphs and Bipartite Graphs
2.3.3 Trees
2.4 Graph Representation
2.4.1 Adjacency Matrix
2.4.2 Adjacency List
2.5 Graph Algorithms
2.5.1 Running Times of Algorithms
2.5.2 Traversal
2.6 Summary
2.7 Exercises
References
PART II NETWORK ANALYSIS
3 Global Network Properties
Ralf Steuer and Gorka Zamora Lo´pez
3.1 Introduction
3.2 Global Properties of Complex Networks
3.2.1 Distance, Average Path Length, and Diameter
3.2.2 Six Degrees of Separation: Concepts of a Small World
3.2.3 The Degree Distribution
3.2.4 Assortative Mixing and Degree Correlations
3.2.5 The Clustering Coefficient
3.2.6 The Matching Index
3.2.7 Network Centralities
3.2.8 Eigenvalues and Spectral Properties of Networks
3.3 Models of Complex Networks
3.3.1 The Erdo¨s–Re´nyi Model
3.3.2 The Watts–Strogatz Model
3.3.3 The Baraba´si–Albert Model
3.3.4 Extensions of the BA Model
3.4 Additional Properties of Complex Networks
3.4.1 Structural Robustness and Attack Tolerance
3.4.2 Modularity, Community Structures and Hierarchies
3.4.3 Subgraphs and Motifs in Networks
3.5 Statistical Testing of Network Properties
3.5.1 Generating Networks and Null Models
3.5.2 The Conceptualization of Cellular Networks
3.5.3 Bipartite Graphs
3.5.4 Correlation Networks
3.6 Summary
3.7 Exercises
References
4 Network Centralities
Dirk Koschu¨tzki
4.1 Introduction
4.2 Centrality Definition and Fundamental Properties
4.2.1 Comparison of Centrality Values
4.2.2 Disconnected Networks
4.3 Degree and Shortest Path-Based Centralities
4.3.1 Degree Centrality
4.3.2 Eccentricity Centrality
4.3.3 Closeness Centrality
4.3.4 Shortest Path Betweenness Centrality
4.3.5 Algorithms
4.3.6 Example
4.4 Feedback-Based Centralities
4.4.1 Katz’s Status Index
4.4.2 Bonacich’s Eigenvector Centrality
4.4.3 PageRank
4.5 Tools
4.6 Summary
4.7 Exercises
References
5 Network Motifs
Henning Schwo¨bbermeyer
5.1 Introduction
5.2 Definitions and Basic Concepts
5.2.1 Definitions
5.2.2 Modeling of Biological Networks
5.2.3 Concepts of Motif Frequency
5.3 Motif Statistics and Motif-Based Network Distance
5.3.1 Determination of Statistical Significance of
Network Motifs
5.3.2 Randomization Algorithm for Generation of
Null Model Networks
5.3.3 Influence of the Null Model on Motif Significance
5.3.4 Limitations of the Null Model on Motif Detection
5.3.5 Measures of Motif Significance and for
Network Comparison
5.4 Complexity of Network Motif Detection
5.4.1 Aspects Affecting the Complexity of Network
Motif Detection
5.4.2 Frequency Estimation by Motif Sampling
5.5 Methods and Tools for Network Motif Analysis
5.5.1 Pajek
5.5.2 Mfinder
5.5.3 MAVisto
5.5.4 FANMOD
5.6 Analyses and Applications of Network Motifs
5.6.1 Network Motifs in Complex Networks
5.6.2 Dynamic Properties of Network Motifs
5.6.3 Higher Order Structures Formed by Network Motifs
5.6.4 Network Comparison Based on Network Motifs
5.6.5 Evolutionary Origin of Network Motifs
5.7 Summary
5.8 Exercises
References
6 Network Clustering
Balabhaskar Balasundaram and Sergiy Butenko
6.1 Introduction
6.2 Notations and Definitions
6.3 Network Clustering Problem
6.4 Clique-Based Clustering
6.4.1 Minimum Clique Partitioning
6.4.2 Min–Max k-Clustering
6.5 Center-Based Clustering
6.5.1 Clustering with Dominating Sets
6.5.2 k-Center Clustering
6.6 Conclusion
6.7 Summary
6.8 Exercises
References
7 Petri Nets
Ina Koch and Monika Heiner
7.1 Introduction
7.2 Qualitative Modeling
7.2.1 The Model
7.2.2 The Behavioral Properties
7.3 Qualitative Analysis
7.3.1 Structural Analysis
7.3.2 Invariant Analysis
7.3.3 MCT-Sets
7.3.4 Dynamic Analysis of General Properties
7.3.5 Dynamic Analysis of Special Properties
7.3.6 Model Validation Criteria
7.4 Quantitative Modeling and Analysis
7.5 Tool Support
7.6 Case Studies
7.7 Summary
7.8 Exercises
References
PART III BIOLOGICAL NETWORKS
8 Signal Transduction and Gene Regulation Networks
Anatolij P. Potapov
8.1 Introduction
8.2 Decisive Role of Regulatory Networks in the Evolution and Existence of Organisms
8.3 Gene Regulatory Network as a System of Many Subnetworks
8.4 Databases on Gene Regulation and Software Tools for Network Analysis
8.5 Peculiarities of Signal Transduction Networks 1
8.6 Topology of Signal Transduction Networks
8.7 Topology of Transcription Networks
8.8 Intercellular Molecular Regulatory Networks
8.9 Summary
8.10 Exercises
References
9 Protein Interaction Networks
Frederik Bo¨rnke
9.1 Introduction
9.2 Detecting Protein Interactions
9.2.1 The Yeast Two-Hybrid System
9.2.2 Affinity Capture of Protein Complexes
9.2.3 Computational Methods to Predict Protein Interactions
9.2.4 Other Ways to Identify Protein Interactions
9.3 Establishing Protein Interaction Networks
9.3.1 Data Storage and Network Generation
9.3.2 Benchmarking High-Throughput Interaction Data
9.4 Analyzing Protein Interaction Networks
9.4.1 Network Topology and Functional Implications
9.4.2 Functional Modules in Protein Interaction
Networks
9.4.3 Evolution of Protein Interaction Networks
9.4.4 Comparative Interactomics
9.5 Summary
9.6 Exercises
References
10 Metabolic Networks
Ma´rcio Rosa da Silva, Jibin Sun, Hongwu Ma, Feng He, and An-Ping Zeng
10.1 Introduction
10.2 Visualization and Graph Representation
10.3 Reconstruction of Genome-Scale Metabolic Networks
10.4 Connectivity and Centrality in Metabolic Networks
10.5 Modularity and Decomposition of Metabolic Networks
10.5.1 Modularity Coefficient
10.5.2 Modularity-Based Decomposition
10.6 Elementary Flux Modes and Extreme Pathways
10.7 Summary
10.8 Exercises
References
11 Phylogenetic Networks
Birgit Gemeinholzer
11.1 Introduction
11.2 Character Selection, Character Coding, and Matrices for Phylogenetic Reconstruction
11.3 Tree Reconstruction Methodologies
11.4 Phylogenetic Networks
11.4.1 Galled Trees
11.4.2 Statistical Parsimony
11.4.3 Median Network
11.4.4 Median-Joining Networks
11.4.5 Pyramids
11.4.6 Example of a Pyramidal Clustering Model
11.4.7 Split Decomposition
11.5 Summary
11.6 Exercises
References
12 Ecological Networks
Ursula Gaedke
12.1 Introduction
12.2 Binary Food Webs
12.2.1 Introduction and Definitions
12.2.2 Descriptors of the Network
12.2.3 Operational Problems
12.2.4 Aims and Results
12.2.5 Conclusion
12.3 Quantitative Trophic Food Webs
12.3.1 Introduction, Definitions, and Database
12.3.2 Multiple Commodities
12.3.3 Descriptors of the Network and Information to be Gained
12.3.4 Conclusion
12.4 Ecological Information Networks
12.5 Summary
12.6 Exercises
References
13 Correlation Networks
Dirk Steinhauser, Leonard Krall, Carsten Mu¨ssig, Dirk Bu¨ ssis,
and Bjo¨rn Usadel
13.1 Introduction
13.2 General Remarks
13.3 Basic Notation
13.3.1 Data, Unit, Variable, and Observation
13.3.2 Sample, Profiles, and Replica Set
13.3.3 Measures of Association
13.3.4 Simple Correlation Measures
13.3.5 Complex Correlation and Association Measures
13.3.6 Probability, Confidence, and Power
13.3.7 Matrices
13.4 Construction and Analyses of Correlation Networks
13.4.1 Data and Profiles
13.4.2 Data Set and Matrix
13.4.3 Correlation Matrix
13.4.4 Network Matrix
13.4.5 Correlation Network Analysis
13.4.6 Interpretation and Validation
13.5 Biological Use of Correlation Networks
13.5.1 The Global Analysis Approach
13.5.2 The Guide Gene Approach
13.5.3 A Simple Coregulation Test: Photosynthesis
13.5.4 A Complex Coregulation Test: Brassinosteroids
13.6 Summary
13.7 Exercises
References
Index
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