Biomolecular Networks

Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.

Alternative techniques and tools for analyzing biomolecularnetworksWith the recent rapid advances in molecular biologyhigh-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 networksystem, 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--Analysisreconstruction, and applications of metabolic networks; modelingand inference of signaling networks; and other topics and newtrendsIn 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 bioinformaticscomputational biology, systems biology, computer science, andapplied mathematics.

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.