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Recent Advances in Biological Network Analysis

Recent Advances in Biological Network Analysis Book
Author : Byung-Jun Yoon,Xiaoning Qian
Publisher : Springer
Release : 2021-03-10
ISBN : 9783030571726
Language : En, Es, Fr & De

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Book Description :

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.

Biological Network Analysis

Biological Network Analysis Book
Author : Pietro Hiram Guzzi,Swarup Roy
Publisher : Elsevier
Release : 2020-05-11
ISBN : 0128193514
Language : En, Es, Fr & De

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Book Description :

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

Thermodynamic Network Analysis of Biological Systems

Thermodynamic Network Analysis of Biological Systems Book
Author : J. Schnakenberg
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 3642963943
Language : En, Es, Fr & De

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Book Description :

This book is devoted to the question: What fundamental ideas and concepts can phys ics contribute to the analysis of complex systems like those in biology and ecolo gy? The book originated from two lectures which I gave during the winter term 1974/75 and the summer term 1976 at the Rheinisch-Westfalische Technische Hoch schule in Aachen. The wish for a lecture with this kind of subject was brought forward by students of physics as well as by those from other disciplines like biology, physiology, and engineering sciences. The students of physics were look ing for ways which might lead them from their monodisciplinary studies into the interdisciplinary field between physics and life sciences. The students from the other disciplines suspected that there might be helpful physical concepts and ideas for the analysis of complex systems they ought to become acquainted with. It is clear that a lecture or a book which tries to realize the expectations of both these groups will meet with difficulties arising from the different train ings and background knowledge of physicists and nonphysicists. For the physicists, I have tried to give a brief description of the biological aspect and significance of a problem wherever it seems necessary and appropriate and as far as a physicist like me feels authorized to do so.

Analyzing Network Data in Biology and Medicine

Analyzing Network Data in Biology and Medicine Book
Author : Nata a Pr ulj,Nataša Pržulj
Publisher : Cambridge University Press
Release : 2019-03-28
ISBN : 1108432239
Language : En, Es, Fr & De

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Book Description :

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

Analysis of Biological Networks

Analysis of Biological Networks Book
Author : Björn H. Junker,Falk Schreiber
Publisher : John Wiley & Sons
Release : 2011-09-20
ISBN : 1118209915
Language : En, Es, Fr & De

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Book Description :

An introduction to biological networks and methods for theiranalysis Analysis of Biological Networks is the first book of itskind to provide readers with a comprehensive introduction to thestructural analysis of biological networks at the interface ofbiology and computer science. The book begins with a brief overviewof biological networks and graph theory/graph algorithms and goeson to explore: global network properties, network centralities,network motifs, network clustering, Petri nets, signal transductionand gene regulation networks, protein interaction networks,metabolic networks, phylogenetic networks, ecological networks, andcorrelation networks. Analysis of Biological Networks is a self-containedintroduction to this important research topic, assumes no expertknowledge in computer science or biology, and is accessible toprofessionals and students alike. Each chapter concludes with asummary of main points and with exercises for readers to test theirunderstanding of the material presented. Additionally, an FTP sitewith links to author-provided data for the book is available fordeeper study. This book is suitable as a resource for researchers in computerscience, biology, bioinformatics, advanced biochemistry, and thelife sciences, and also serves as an ideal reference text forgraduate-level courses in bioinformatics and biologicalresearch.

Computational Network Analysis with R

Computational Network Analysis with R Book
Author : Matthias Dehmer,Yongtang Shi,Frank Emmert-Streib
Publisher : John Wiley & Sons
Release : 2016-12-12
ISBN : 3527339582
Language : En, Es, Fr & De

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Book Description :

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.

Weighted Network Analysis

Weighted Network Analysis Book
Author : Steve Horvath
Publisher : Springer Science & Business Media
Release : 2011-04-30
ISBN : 9781441988195
Language : En, Es, Fr & De

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Book Description :

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.

Emergence of Communication in Socio Biological Networks

Emergence of Communication in Socio Biological Networks Book
Author : Anamaria Berea
Publisher : Springer
Release : 2017-12-16
ISBN : 331964565X
Language : En, Es, Fr & De

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Book Description :

This book integrates current advances in biology, economics of information and linguistics research through applications using agent-based modeling and social network analysis to develop scenarios of communication and language emergence in the social aspects of biological communications. The book presents a model of communication emergence that can be applied both to human and non-human living organism networks. The model is based on economic concepts and individual behavior fundamental for the study of trust and reputation networks in social science, particularly in economics; it is also based on the theory of the emergence of norms and historical path dependence that has been influential in institutional economics. Also included are mathematical models and code for agent-based models to explore various scenarios of language evolution, as well as a computer application that explores language and communication in biological versus social organisms, and the emergence of various meanings and grammars in human networks. Emergence of Communication in Socio-Biological Networks offers both a completely novel approach to communication emergence and language evolution and provides a path for the reader to explore various scenarios of language and communication that are not constrained to the human networks alone. By illustrating how computational social science and the complex systems approach can incorporate multiple disciplines and offer an integrated theory-model approach to the evolution of language, the book will be of interest to researchers working with computational linguistics, mathematical linguistics, and complex systems.

Models of Biological Networks and Software Tool for Network Analysis

Models of Biological Networks and Software Tool for Network Analysis Book
Author : Aleksandar Stevanović
Publisher : Unknown
Release : 2010
ISBN : 9781124125015
Language : En, Es, Fr & De

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Book Description :

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.

Biological Networks

Biological Networks Book
Author : Fran‡ois K‚pŠs
Publisher : World Scientific
Release : 2007
ISBN : 981270695X
Language : En, Es, Fr & De

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Book Description :

This volume presents a timely and comprehensive overview of biological networks at all organization levels in the spirit of the complex system approach. It discusses the transversal issues and fundamental principles as well as the overall structure, dynamics, and modeling of a wide array of biological networks at the molecular, cellular, and population levels. Anchored in both empirical data and a strong theoretical background, the book therefore lends valuable credence to the complex systems approach.

New Frontiers of Network Analysis in Systems Biology

New Frontiers of Network Analysis in Systems Biology Book
Author : Avi Ma'ayan,Ben D. MacArthur
Publisher : Springer Science & Business Media
Release : 2012-06-25
ISBN : 9400743300
Language : En, Es, Fr & De

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Book Description :

The rapidly developing field of systems biology is influencing many aspects of biological research and is expected to transform biomedicine. Some emerging offshoots and specialized branches in systems biology are receiving particular attention and are becoming highly active areas of research. This collection of invited reviews describes some of the latest cutting-edge experimental and computational advances in these emerging sub-fields of systems biology. In particular, this collection focuses on the study of mammalian embryonic stem cells; new technologies involving mass-spectrometry proteomics; single cell measurements; methods for modeling complex stochastic systems; network-based classification algorithms; and the revolutionary emerging field of systems pharmacology.

Statistical and Evolutionary Analysis of Biological Networks

Statistical and Evolutionary Analysis of Biological Networks Book
Author : Michael P. H. Stumpf
Publisher : World Scientific
Release : 2010
ISBN : 1848164343
Language : En, Es, Fr & De

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Book Description :

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. Sample Chapter(s). Chapter 1: A Network Analysis Primer (350 KB). Contents: A Network Analysis Primer (M P H Stumpf & C Wiuf); Evolutionary Analysis of Protein Interaction Networks (C Wiuf & O Ratmann); Motifs in Biological Networks (F Schreiber & H SchwAbbermeyer); Bayesian Analysis of Biological Networks: Clusters, Motifs, Cross-Species Correlations (J Berg & M Lnssig); Network Concepts and Epidemiological Models (R R Kao & I Z Kiss); Evolutionary Origin and Consequences of Design Properties of Metabolic Networks (T Pfeiffer & S Bonhoeffer); Protein Interactions from an Evolutionary Perspective (F Pazos & A Valencia); Statistical Null Models for Biological Network Analysis (W P Kelly et al.). Readership: Academics, researchers, postgraduates and advanced undergraduates in bioinformatics. Biologists, mathematicians/statisticians, physicists and computer scientists.

Fundamentals Of Network Biology

Fundamentals Of Network Biology Book
Author : Zhang Wenjun
Publisher : World Scientific
Release : 2018-05-16
ISBN : 1786345102
Language : En, Es, Fr & De

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Book Description :

As the first comprehensive title on network biology, this book covers a wide range of subjects including scientific fundamentals (graphs, networks, etc) of network biology, construction and analysis of biological networks, methods for identifying crucial nodes in biological networks, link prediction, flow analysis, network dynamics, evolution, simulation and control, ecological networks, social networks, molecular and cellular networks, network pharmacology and network toxicology, big data analytics, and more. Across 12 parts and 26 chapters, with Matlab codes provided for most models and algorithms, this self-contained title provides an in-depth and complete insight on network biology. It is a valuable read for high-level undergraduates and postgraduates in the areas of biology, ecology, environmental sciences, medical science, computational science, applied mathematics, and social science. Contents: Mathematical Fundamentals: Fundamentals of Graph TheoryGraph AlgorithmsFundamentals of Network TheoryOther FundamentalsCrucial Nodes/Subnetworks/Modules, Network Types, and Structural Comparison: Identification of Crucial Nodes and Subnetworks/ModulesDetection of Network TypesComparison of Network StructureNetwork Dynamics, Evolution, Simulation and Control: Network DynamicsNetwork Robustness and Sensitivity AnalysisNetwork ControlNetwork EvolutionCellular AutomataSelf-OrganizationAgent-based ModelingFlow Analysis: Flow/Flux AnalysisLink and Node Prediction: Link Prediction: Sampling-based MethodsLink Prediction: Structure- and Perturbation-based MethodsLink Prediction: Node-Similarity-based MethodsNode PredictionNetwork Construction: Construction of Biological NetworksPharmacological and Toxicological Networks: Network Pharmacology and ToxicologyEcological Networks: Food WebsMicroscopic Networks: Molecular and Cellular NetworksSocial Networks: Social Network AnalysisSoftware: Software for Network AnalysisBig Data Analytics: Big Data Analytics for Network Biology Readership: Advanced undergraduates and graduate students and researchers in biology, ecology, pharmacology, applied mathematics, computational science, etc. Keywords: Network Biology;Network Analysis;Food Webs;Molecular Networks;Social Networks;Network Pharmacology;Link Prediction;Network Dynamics;Big Data Analytics;Software;Models;Algorithms;Nodes;LinksReview:0

Clustering and Network Analysis with Biological Applications

Clustering and Network Analysis with Biological Applications Book
Author : Konstantin Voevodski
Publisher : Unknown
Release : 2011
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Clustering and network analysis are important areas of research in Computer Science and other disciplines. Clustering is broadly defined as finding sets of similar objects. It has many applications, such as finding groups of similar buyers given their product preferences, and finding groups of similar proteins given their sequences. Network analysis considers data represented by a collection of nodes (vertices), and edges that link these nodes. The structure of the network is studied to find central nodes, identify nodes that are similar to a particular vertex, and find well-connected groups of vertices. The World Wide Web and online social networks are some of the best studied networks today. Network analysis can also be applied to biological networks where nodes are proteins and edges represent relationships or interactions between them. The size of real-world data sets presents many challenges to computational techniques that interpret them. A classic clustering problem is to divide the data set into groups, given the pairwise distances between the objects. However, computing all the pairwise distances may be infeasible if the data set is very large. In this thesis we consider clustering in a limited information setting where we do not know the distances between the objects in advance, and instead must query them during the execution of the algorithm. We present algorithms that find an accurate clustering in this setting using few queries. The networks that we encounter in practice are quite large as well, making computations on the entire network difficult. In this thesis we present techniques for locally exploring networks, which are efficient but still give meaningful information about the local structure of the graph. We develop several tools for locally exploring a network, and show that they give meaningful results when applied to protein networks.

Summarizing Biological Networks

Summarizing Biological Networks Book
Author : Sourav S. Bhowmick,Boon-Siew Seah
Publisher : Springer
Release : 2017-04-17
ISBN : 331954621X
Language : En, Es, Fr & De

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Book Description :

This book focuses on the data mining, systems biology, and bioinformatics computational methods that can be used to summarize biological networks. Specifically, it discusses an array of techniques related to biological network clustering, network summarization, and differential network analysis which enable readers to uncover the functional and topological organization hidden in a large biological network. The authors also examine crucial open research problems in this arena. Academics, researchers, and advanced-level students will find this book to be a comprehensive and exceptional resource for understanding computational techniques and their applications for a summary of biological networks.

Network Biology

Network Biology Book
Author : Wenjun Zhang
Publisher : Nova Science Pub Incorporated
Release : 2013-01-01
ISBN : 9781626189423
Language : En, Es, Fr & De

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Book Description :

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.

Networks in Systems Biology

Networks in Systems Biology Book
Author : Fabricio Alves Barbosa da Silva,Nicolas Carels,Marcelo Trindade dos Santos,Francisco José Pereira Lopes
Publisher : Springer
Release : 2020-11-29
ISBN : 9783030518615
Language : En, Es, Fr & De

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Book Description :

This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.

Unraveling Biological Mechanisms Using Network Analysis

Unraveling Biological Mechanisms Using Network Analysis Book
Author : Bryan Killinger
Publisher : Unknown
Release : 2017
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Unraveling Biological Mechanisms Using Network Analysis book written by Bryan Killinger, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Correlation based network analysis of cancer metabolism

Correlation based network analysis of cancer metabolism Book
Author : Emily G. Armitage,Helen L. Kotze,Kaye J. Williams
Publisher : Springer
Release : 2014-05-12
ISBN : 1493906151
Language : En, Es, Fr & De

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Book Description :

With the rise of systems biology as an approach in biochemistry research, using high throughput techniques such as mass spectrometry to generate metabolic profiles of cancer metabolism is becoming increasingly popular. There are examples of cancer metabolic profiling studies in the academic literature; however they are often only in journals specific to the metabolomics community. This book will be particularly useful for post-graduate students and post-doctoral researchers using this pioneering technique of network-based correlation analysis. The approach can be adapted to the analysis of any large scale metabolic profiling experiment to answer a range of biological questions in a range of species or for a range of diseases.

Computational Analysis of Biological Networks

Computational Analysis of Biological Networks Book
Author : Giovanni Scardoni
Publisher : LAP Lambert Academic Publishing
Release : 2011-12
ISBN : 9783846590089
Language : En, Es, Fr & De

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Book Description :

Characterizing, describing, and extracting information from a network is by now one of the main goals of science, since the study of network currently draws the attention of several fields of research, as biology, economics, social science, computer science and so on. The main goal is to analyze networks in order to extract their emergent properties and to understand functionality of such complex systems. This work concerns the analysis of biological networks and the two main approaches are treated: the first based on the study of their topological structure, the second based on the dynamic properties of the system described by a network. Original methods are presented to extract information from a network through both static and dynamic approaches opening new perspectives in biological network analysis.