Biological Network Analysis

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Biological Network Analysis

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Author : Pietro Hiram Guzzi
language : en
Publisher: Academic Press
Release Date : 2020-05-12

Biological Network Analysis written by Pietro Hiram Guzzi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-12 with Science categories.

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.

Recent Advances In Biological Network Analysis

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Author : Byung-Jun Yoon
language : en
Publisher: Springer Nature
Release Date : 2021-01-13

Recent Advances In Biological Network Analysis written by Byung-Jun Yoon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-13 with Medical categories.

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.

Analysis Of Biological Networks

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Author : Björn H. Junker
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20

Analysis Of Biological Networks written by Björn H. Junker and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Computers categories.

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

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Author : Pietro Hiram Guzzi
language : en
Publisher: Elsevier
Release Date : 2020-05-11

Biological Network Analysis written by Pietro Hiram Guzzi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-11 with Science categories.

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

Computational Network Analysis With R

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Author : Matthias Dehmer
language : en
Publisher: John Wiley & Sons
Release Date : 2016-07-22

Computational Network Analysis With R written by Matthias Dehmer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-22 with Medical categories.

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.

Deep Learning For Biological Network Analysis

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Author : Jianye Hao
language : en
Publisher: Frontiers Media SA
Release Date : 2022-02-07

Deep Learning For Biological Network Analysis written by Jianye Hao and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-07 with Science categories.

Weighted Network Analysis

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Author : Steve Horvath
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-30

Weighted Network Analysis written by Steve Horvath and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-30 with Science categories.

High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.

Models Of Biological Networks And Software Tool For Network Analysis

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Author : Aleksandar Stevanović
language : en
Publisher:
Release Date : 2010

Models Of Biological Networks And Software Tool For Network Analysis written by Aleksandar Stevanović and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Understanding the nature of complex networks of protein-protein interactions (PPIs) is one of the most challenging tasks in modern computational biology. Because protein-protein interactions carry an important role in a large number of cellular functions, the topology of PPI networks shows structural patterns and regularities imposed by evolution. In order to understand the structure of PPI networks, and thus infer the nature of biological processes, it is necessary to develop models of PPI networks that would closely correspond to their real-world counterparts. For the purposes of network analysis, PPI networks are presented as graphs, where each node corresponds to a unique protein and each edge corresponds to an interaction between two proteins. Random graph models have been used to model PPI networks and in this thesis, we propose a novel random graph model that takes into account evolutionary processes of gene duplication and mutation in an attempt to provide the best fit for PPI networks, while utilizing the basic concept of geometric graphs, which has been shown to be the best fitting model so far for eukariotic species. In addition to network modeling, researchers need software tools in order to effectively perform different types of network analysis such as network comparison, alignment and clustering. While a large number of such software tools exists, researchers are limited by the number of models, methods and heuristics that existing software implements and furthermore restricted by the lack of automation which hinders practical applications for comprehensive network analysis. In this thesis, we introduce GraphCrunch 2 - a software tool to automate network model generation and analysis. It implements seven most popular random network models and compares them with the experimental data using commonly used network properties and more advanced, graphlet-based, heuristics. In addition, GraphCrunch 2 implements GRAphALigner (GRAAL) algorithm for purely topological network alignment, which can be applied to align any pair of networks, exposing regions of topological and functional similarities. Finally, GraphCrunch 2 implements k-medoids algorithm for clustering nodes in PPI network based solely on their topology.

Statistical And Evolutionary Analysis Of Biological Networks

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Author : Michael P H Stumpf
language : en
Publisher: World Scientific
Release Date : 2009-12-23

Statistical And Evolutionary Analysis Of Biological Networks written by Michael P H Stumpf and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-23 with Science categories.

Networks provide a very useful way to describe a wide range of different data types in biology, physics and elsewhere. Apart from providing a convenient tool to visualize highly dependent data, networks allow stringent mathematical and statistical analysis.In recent years, much progress has been achieved to interpret various types of biological network data such as transcriptomic, metabolomic and protein interaction data as well as epidemiological data. Of particular interest is to understand the organization, complexity and dynamics of biological networks and how these are influenced by network evolution and functionality.This book reviews and explores statistical, mathematical and evolutionary theory and tools in the understanding of biological networks. The book is divided into comprehensive and self-contained chapters, each of which focuses on an important biological network type, explains concepts and theory and illustrates how these can be used to obtain insight into biologically relevant processes and questions. There are chapters covering metabolic, transcriptomic, protein interaction and epidemiological networks as well as chapters that deal with theoretical and conceptual material. The authors, who contribute to the book, are active, highly regarded and well-known in the network community./a

Network Biology

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Author : WenJun Zhang
language : en
Publisher: Nova Science Publishers
Release Date : 2013

Network Biology written by WenJun Zhang and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Biometry categories.

Biological network analysis is a fast moving science. Many core scientific issues; for example, ecological structure, coevolution, coextinction and biodiversity conservation in ecology, cancer development and metabolic regulation in health science, etc., are expected to be addressed by network analysis. Network analysis is becoming the core methodology to treat complex biological systems. With the quick development of this science, more and more papers on biological networks are published. This book includes such theories and methods of network biology as methodology of social network analyses, construction of statistic networks, phylogenetic networks, multi-stable and oscillatory biological networks, creation of real networks with expected degree distribution, forest ecosystem model, etc. Chapters are contributed by 15 scientists from the USA, Canada, New Zealand, China, Sweden, and Spain, in the areas of computational science and life sciences. It will provide researchers with various aspects of the latest advances in network biology. It is a valuable reference for scientists, university teachers and graduate students in biology, health science, ecology, social science, applied mathematics and computational science.