Analysis of Biological Networks

Analysis of Biological Networks

Author: Björn H. Junker

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 278

ISBN-13: 1118209915

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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.


Biological Network Analysis

Biological Network Analysis

Author: Pietro Hiram Guzzi

Publisher: Elsevier

Published: 2020-05-11

Total Pages: 212

ISBN-13: 0128193514

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Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource. - Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models - Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes - Includes a discussion of various graph theoretic and data analytics approaches


Biological Networks and Pathway Analysis

Biological Networks and Pathway Analysis

Author: Tatiana V. Tatarinova

Publisher: Humana Press

Published: 2017-08-29

Total Pages: 509

ISBN-13: 9781493970254

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In this volume, expert practitioners present a compilation of methods of functional data analysis (often referred to as “systems biology”) and its applications in drug discovery, medicine, and basic disease research. It covers such important issues as the elucidation of protein, compound and gene interactions, as well as analytical tools, including networks, interactome and ontologies, and clinical applications of functional analysis. As a volume in the highly successful Methods in Molecular Biology series, this work provides detailed description and hands-on implementation advice. Reputable, comprehensive, and cutting-edge, Biological Networks and Pathway Analysis presents both “wet lab” experimental methods and computational tools in order to cover a broad spectrum of issues in this fascinating new field.


Recent Advances in Biological Network Analysis

Recent Advances in Biological Network Analysis

Author: Byung-Jun Yoon

Publisher: Springer Nature

Published: 2021-01-13

Total Pages: 220

ISBN-13: 3030571734

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This book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights.


Thermodynamic Network Analysis of Biological Systems

Thermodynamic Network Analysis of Biological Systems

Author: J. Schnakenberg

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 157

ISBN-13: 3642679714

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The first edition of this book was greeted with broad interest from readers en gaged in various disciplines of biophysics. I received many stimulating and en couraging responses, however, some of the book's reviewers wanted to stress the fact that an extensive literature of network theory was not included or reported in the book. But the main aspect of the book is intended to be substantive rather than methodical: networks simply serve as a remedy for doing some first steps in analysing and modelling complex biological systems. For an advanced stage in the investigation of a particular system it may be appropriate to replace the pheno menological network method by more detailed techniques like statistical equations or computer simulations. According to this intention, the second edition of the book has been enlarged by further biological examples for network analysis, not by more network theory. There is a completely new section on a network model for photoreception. For this section I am obliged to J. Tiedge who did most of the detailed calculation and to my colleague Professor Stieve with whom we have had a very fruitful cooperation. Also I would like to mention that this work has been sponsored by the "Deutsche Forschungsgemei nschaft" i n the "Sonderforschungsberei ch 160". Recent results for excitable systems represented by feedback networks have also been included in the second edition, especially for limit cycle networks.


Introduction to Biological Networks

Introduction to Biological Networks

Author: Alpan Raval

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 329

ISBN-13: 1420010360

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The new research area of genomics-inspired network biology lacks an introductory book that enables both physical/computational scientists and biologists to obtain a general yet sufficiently rigorous perspective of current thinking. Filling this gap, Introduction to Biological Networks provides a thorough introduction to genomics-inspired network bi


Networks of Networks in Biology

Networks of Networks in Biology

Author: Narsis A. Kiani

Publisher: Cambridge University Press

Published: 2021-04

Total Pages: 215

ISBN-13: 1108428878

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Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.


Computational Network Analysis with R

Computational Network Analysis with R

Author: Matthias Dehmer

Publisher: John Wiley & Sons

Published: 2016-12-12

Total Pages: 364

ISBN-13: 3527339582

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This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.


Methods in Bioengineering

Methods in Bioengineering

Author: Arul Jayaraman

Publisher: Artech House

Published: 2009

Total Pages: 329

ISBN-13: 1596934069

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"This cutting-edge volume provides a detailed look at the two main aspects of systems biology: the design of sophisticated experimental methods and the development of complex models to analyze the data. Focusing on methods that are being used to solve current problems in biomedical science and engineering, this comprehensive, richly illustrated resource shows you how to: design of state-of-the art methods for analyzing biological systems Implement experimental approaches for investigating cellular behavior in health and disease; use algorithms and modeling techniques for quantitatively describing biomedical problems; and integrate experimental and computational approaches for a more complete view of biological systems." --Book Jacket.


Analyzing Network Data in Biology and Medicine

Analyzing Network Data in Biology and Medicine

Author: Nataša Pržulj

Publisher: Cambridge University Press

Published: 2019-03-28

Total Pages: 647

ISBN-13: 1108432239

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Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.