Chen / Wang / Zhang Biomolecular Networks

Methods and Applications in Systems Biology
1. Auflage 2009
ISBN: 978-0-470-48805-8
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, Band 1, 416 Seiten, E-Book

Reihe: Wiley Series in Bioinformatics

Alternative techniques and tools for analyzing biomolecularnetworks
With the recent rapid advances in molecular biology,high-throughput experimental methods have resulted in enormousamounts of data that can be used to study biomolecular networks inliving organisms. With this development has come recognition of thefact that a complicated living organism cannot be fully understoodby merely analyzing individual components. Rather, it is theinteractions of components or biomolecular networks that areultimately responsible for an organism's form and function. Thisbook addresses the important need for a new set of computationaltools to reveal essential biological mechanisms from a systemsbiology approach.
Readers will get comprehensive coverage of analyzingbiomolecular networks in cellular systems based on availableexperimental data with an emphasis on the aspects of network,system, integration, and engineering. Each topic is treated indepth with specific biological problems and novel computationalmethods:
* GENE NETWORKS--Transcriptional regulation; reconstructionof gene regulatory networks; and inference of transcriptionalregulatory networks
* PROTEIN INTERACTION NETWORKS--Prediction of protein-proteininteractions; topological structure of biomolecular networks;alignment of biomolecular networks; and network-based prediction ofprotein function
* METABOLIC NETWORKS AND SIGNALING NETWORKS--Analysis,reconstruction, and applications of metabolic networks; modelingand inference of signaling networks; and other topics and newtrends
In addition to theoretical results and methods, manycomputational software tools are referenced and available from theauthors' Web sites. Biomolecular Networks is an indispensablereference for researchers and graduate students in bioinformatics,computational biology, systems biology, computer science, andapplied mathematics.

Autoren/Hrsg.

Chen, Luonan

Wang, Rui-Sheng

Zhang, Xiang-Sun

Inhaltsverzeichnis

PREFACE.
ACKNOWLEDGMENTS.
LIST OF ILLUSTRATIONS.
ACRONYMS.
1 Introduction.
1.1 Basic Concepts in Molecular Biology.
1.2 Biomolecular Networks in Cells.
1.3 Network Systems Biology.
1.4 About This Book.
I GENE NETWORKS.
2 Transcription Regulation: Networks and Models.
2.1 Transcription Regulation and Gene Expression.
2.2 Networks in Transcription Regulation.
2.3 Nonlinear Models Based on Biochemical Reactions.
2.4 Integrated Models for Regulatory Networks.
2.5 Summary.
3 Reconstruction of Gene Regulatory Networks.
3.1 Mathematical Models of Gene Regulatory Network.
3.2 Reconstructing Gene Regulatory Networks.
3.3 Inferring Gene Networks from Multiple Datasets.
3.4 Gene Network-Based Drug Target Identification.
3.5 Summary.
4 Inference of Transcriptional Regulatory Networks.
4.1 Predicting TF Binding Sites and Promoters.
4.2 Inference of Transcriptional Interactions.
4.3 Identifying Combinatorial Regulations of TFs.
4.4 Inferring Cooperative Regulatory Networks.
4.5 Prediction of Transcription Factor Activity.
4.6 Summary.
II PROTEIN INTERACTION NETWORKS.
5 Prediction of Protein-Protein Interactions.
5.1 Experimental Protein-Protein Interactions.
5.2 Prediction of Protein-Protein Interactions.
5.3 Protein Interaction Prediction Based on MultidomainPairs.
5.4 Domain Interaction Prediction Methods.
5.5 Summary.
6 Topological Structure of Biomolecular Networks.
6.1 Statistical Properties of Biomolecular Networks.
6.2 Evolution of Protein Interaction Networks.
6.3 Hubs, Motifs, and Modularity in Biomolecular Networks.
6.4 Explorative Roles of Hubs and Network Motifs.
6.5 Modularity Evaluation of Biomolecular Networks.
6.6 Summary.
7 Alignment of Biomolecular Networks.
7.1 Biomolecular Networks from Multiple Species.
7.2 Pairwise Alignment of Biomolecular Networks.
7.3 Network Alignment by Mathematical Programming.
7.4 Multiple Alignment of Biomolecular Networks.
7.5 Subnetwork and Pathway Querying.
7.6 Summary.
8 Network-Based Prediction of Protein Function.
8.1 Protein Function and Annotation.
8.2 Protein Functional Module Detection.
8.3 Functional Linkage for Protein Function Annotation.
8.4 Protein Function Prediction from High-Throughput Data.
8.5 Function Annotation Methods for Domains.
8.6 Summary.
III METABOLIC NETWORKS AND SIGNALING NETWORKS.
9 Metabolic Networks: Analysis, Reconstruction, andApplication.
9.1 Cellular Metabolism and Metabolic Pathways.
9.2 Metabolic Network Analysis and Modeling.
9.3 Reconstruction of Metabolic Networks.
9.4 Drug Target Detection in Metabolic Networks.
9.5 Summary.
10 Signaling Networks: Modeling and Inference.
10.1 Signal Transduction in Cellular Systems.
10.2 Modeling of Signal Transduction Pathways.
10.3 Inferring Signaling Networks from High-Throughput Data.
10.4 Inferring Signaling Networks by Linear Programming.
10.5 Inferring Signaling Networks from ExperimentalEvidence.
10.6 Summary.
11 Other Topics and New Trends.
11.1 Network-Based Protein Structural Analysis.
11.2 Integration of Biomolecular Networks.
11.3 Posttranscriptional Regulation of Noncoding RNAs.
11.4 Biomolecular Interactions and Human Diseases.
11.5 Summary.
REFERENCES.
INDEX.

Über Autor(innen)

LUONAN CHEN, PhD, is a full professor in the Department ofElectrical Engineering and Electronics, Osaka Sangyo University,Osaka, Japan, and he is also the founding director of Institute ofSystems Biology, Shanghai University, Shanghai, China. Dr. Chen'sfields of interest include systems biology, bioinformatics, andnonlinear dynamics.
RUI-SHENG WANG, PhD, is an assistant professor in theSchool of Information, Renmin University of China. Dr. Wang'sresearch interests include bioinformatics, computational systemsbiology, and complex networks.
XIANG-SUN ZHANG is a full research professor in theInstitute of Applied Math-ematics, Chinese Academy of Sciences.Professor Zhang's research interests include bioinformatics,systems biology, optimization theory, and related computationalmathematics.