Analysis of Biological Networks

An introduction to biological networks and methods for their analysis
Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks.
Analysis of Biological Networks is a self–contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author–provided data for the book is available for deeper study.
This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate–level courses in bioinformatics and biological research.

Spis treści:
Foreword.
Preface.
Contributors.
PART I INTRODUCTION 1
1 Networks in Biology (Bjorn H. Junker).
1.1 Introduction.
1.2 Biology.
1.3 Systems Biology.
1.4 Properties of Biological Networks.
1.5 Summary.
1.6 Exercises.
References.
2 Graph Theory (Falk Schreiber).
2.1 Introduction.
2.2 Basic Notation.
2.3 Special Graphs. 
2.4 Graph Representation.
2.5 Graph Algorithms.
2.6 Summary.
2.7 Exercises.
References.
PART II NETWORK ANALYSIS.
3 Global Network Properties (Ralf Steue r and Gorka Zamora Lopez).
3.1 Introduction.
3.2 Global Properties of Complex Networks.
3.3 Models of Complex Networks.
3.4 Additional Properties of Complex Networks.
3.5 Statistical Testing of Network Properties.
3.6 Summary.
3.7 Exercises.
References.
4 Network Centralities (Dirk Koschutzki).
4.1 Introduction.
4.2 Centrality Definition and Fundamental Properties.
4.3 Degree and Shortest Path–Based Centralities.
4.4 Feedback–Based Centralities.
4.5 Tools.
4.6 Summary.
4.7 Exercises.
References.
5 Network Motifs (Henning Schwobbermeyer).
5.1 Introduction.
5.2 Definitions and Basic Concepts.
5.3 Motif Statistics and Motif–Based Network Distance.
5.4 Complexity of Network Motif Detection.
5.5 Methods and Tools for Network Motif Analysis.
5.6 Analyses and Applications 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.
6.5 Center–Based 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.
7.3 Qualitative Analysis.
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.
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 Bornke).
9.1 Introduction.
9.2 Detecting Protein Interactions.
9.3 Establishing Protein Interaction Networks.
9.4 Analyzing Protein Interaction Networks.
9.5 Summary.
9.6 Exercises.
References.
10 Metabolic Networks (Marcio 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.
10.6 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.
11.5 Summary.
11.6 Exercises.
References.
12 Ecological Networks (Ursula Gaedke).
12.1 Introduction.
12.2 Binary Food Webs.
12.3 Quantitative Trophic Food Webs.
12.4 Ecological Information Networks.
12.5 Summary.
12.6 Exercises.
References.
13 Correlation Networks (Dirk Steinhauser, Leonard Krall, Carsten Mussig, Dirk Bussis, and Bjorn Usadel).
13.1 Introduction.
13.2 General Remarks.
13.3 Basic Notation.
13.4 Construction and Analyses of Correlation Networks.
13.5 Biological Use of Correlation Networks.
13.6 Summary.
13.7 Exercises.
References.
Index.

Nota biograficzna:

Björn H. Junker is a biologist with a strong background in bioinformatics. His current research activities include the quantitative analysis and modeling of metabolic networks, as well as pathway databases and visual data mining. Mr. Junker has been at the Leibniz Institute of Plant Genetics and Crop Plant Research in Germany since 2003. He worked at Brookhaven National Laboratory in New York during 2006 and was appointed as project leader at the Leibniz Institute in 2007.
Falk Schreiber is a computer scientist who has worked in bioinformatics for more than ten years. His current research areas include modeling, analysis, and visualization of biological networks; graph algorithms; and data exploration and information visualization in the life sciences. Since 2003, he has been head of the Network Analysis Research Group at the Leibniz Institute of Plant Genetics and Crop Plant Research. He was appointed professor of bioinformatics at the Martin Luther University Halle–Wittenberg, Germany, in 2007.

Okładka tylna:

An introduction to biological networks and methods for their analysis
Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks.
Analysis of Biological Networks is a self–contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author–provided data for the book is available for deeper study.
This book is suitable as a