Biological Network Analysis

Biological Network Analysis
Author: Pietro Hiram Guzzi,Swarup Roy
Publsiher: Elsevier
Total Pages: 210
Release: 2020-05-11
ISBN 10: 0128193514
ISBN 13: 9780128193518
Language: EN, FR, DE, ES & NL

Biological Network Analysis Book Review:

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

Analysis of Biological Networks

Analysis of Biological Networks
Author: Björn H. Junker,Falk Schreiber
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2011-09-20
ISBN 10: 1118209915
ISBN 13: 9781118209912
Language: EN, FR, DE, ES & NL

Analysis of Biological Networks Book Review:

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.

Recent Advances in Biological Network Analysis

Recent Advances in Biological Network Analysis
Author: Byung-Jun Yoon,Xiaoning Qian
Publsiher: Springer Nature
Total Pages: 217
Release: 2021-01-13
ISBN 10: 3030571734
ISBN 13: 9783030571733
Language: EN, FR, DE, ES & NL

Recent Advances in Biological Network Analysis Book Review:

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
Author: Pietro Hiram Guzzi,Swarup Roy
Publsiher: Academic Press
Total Pages: 210
Release: 2020-05-26
ISBN 10: 0128193506
ISBN 13: 9780128193501
Language: EN, FR, DE, ES & NL

Biological Network Analysis Book Review:

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

Statistical and Evolutionary Analysis of Biological Networks

Statistical and Evolutionary Analysis of Biological Networks
Author: Michael P. H. Stumpf,Carsten Wiuf
Publsiher: World Scientific
Total Pages: 170
Release: 2010
ISBN 10: 1848164335
ISBN 13: 9781848164338
Language: EN, FR, DE, ES & NL

Statistical and Evolutionary Analysis of Biological Networks Book Review:

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.

Computational Network Analysis with R

Computational Network Analysis with R
Author: Matthias Dehmer,Yongtang Shi,Frank Emmert-Streib
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2016-07-22
ISBN 10: 3527694404
ISBN 13: 9783527694402
Language: EN, FR, DE, ES & NL

Computational Network Analysis with R Book Review:

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.

Analyzing Network Data in Biology and Medicine

Analyzing Network Data in Biology and Medicine
Author: Nata a Pr ulj,Nataša Pržulj
Publsiher: Cambridge University Press
Total Pages: 672
Release: 2019-03-28
ISBN 10: 1108432239
ISBN 13: 9781108432238
Language: EN, FR, DE, ES & NL

Analyzing Network Data in Biology and Medicine Book Review:

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

Computational Network Analysis with R

Computational Network Analysis with R
Author: Matthias Dehmer,Yongtang Shi,Frank Emmert-Streib
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2016-08-09
ISBN 10: 3527694374
ISBN 13: 9783527694372
Language: EN, FR, DE, ES & NL

Computational Network Analysis with R Book Review:

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.

A Practical Guide To Cancer Systems Biology

A Practical Guide To Cancer Systems Biology
Author: Juan Hsueh-fen,Huang Hsuan-cheng
Publsiher: World Scientific
Total Pages: 152
Release: 2017-11-29
ISBN 10: 9813229160
ISBN 13: 9789813229167
Language: EN, FR, DE, ES & NL

A Practical Guide To Cancer Systems Biology Book Review:

Systems biology combines computational and experimental approaches to analyze complex biological systems and focuses on understanding functional activities from a systems-wide perspective. It provides an iterative process of experimental measurements, data analysis, and computational simulation to model biological behavior. This book provides explained protocols for high-throughput experiments and computational analysis procedures central to cancer systems biology research and education. Readers will learn how to generate and analyze high-throughput data, therapeutic target protein structure modeling and docking simulation for drug discovery. This is the first practical guide for students and scientists who wish to become systems biologists or utilize the approach for cancer research. Contents: Introduction to Cancer Systems Biology (Hsueh-Fen Juan and Hsuan-Cheng Huang)Transcriptome Analysis: Library Construction (Hsin-Yi Chang and Hsueh-Fen Juan)Quantitative Proteome: The Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) (Yi-Hsuan Wu and Hsueh-Fen Juan)Phosphoproteome: Sample Preparation (Chia-Wei Hu and Hsueh-Fen Juan)Transcriptomic Data Analysis: RNA-Seq Analysis Using Galaxy (Chia-Lang Hsu and Chantal Hoi Yin Cheung)Proteomic Data Analysis: Functional Enrichment (Hsin-Yi Chang and Hsueh-Fen Juan)Phosphorylation Data Analysis (Chia-Lang Hsu and Wei-Hsuan Wang)Pathway and Network Analysis (Chen-Tsung Huang and Hsueh-Fen Juan)Dynamic Modeling (Yu-Chao Wang)Protein Structure Modeling (Chia-Hsien Lee and Hsueh-Fen Juan)Docking Simulation (Chia-Hsien Lee and Hsueh-Fen Juan) Readership: Graduate students and researchers entering the cancer systems biology field. Keywords: Systems Biology;Transcriptomics;Proteomics;Network Biology;Dynamic Modeling;Protein Structure Modeling;Docking Simulation;BioinformaticsReview: Key Features: Written by two active researchers in the fieldCovers both experimental and computational areas in cancer systems biologyStep-by-step instructions help beginners who are interested in creating biological data and analyzing the data by themselvesReaders will gain the skills to generate and analyze omics data and discover potential therapeutic targets and drug candidates

Weighted Network Analysis

Weighted Network Analysis
Author: Steve Horvath
Publsiher: Springer Science & Business Media
Total Pages: 421
Release: 2011-04-30
ISBN 10: 9781441988195
ISBN 13: 144198819X
Language: EN, FR, DE, ES & NL

Weighted Network Analysis Book Review:

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.

Thermodynamic Network Analysis of Biological Systems

Thermodynamic Network Analysis of Biological Systems
Author: J. Schnakenberg
Publsiher: Springer Science & Business Media
Total Pages: 143
Release: 2012-12-06
ISBN 10: 3642963943
ISBN 13: 9783642963940
Language: EN, FR, DE, ES & NL

Thermodynamic Network Analysis of Biological Systems Book Review:

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.

Biological Networks

Biological Networks
Author: Fran‡ois K‚pŠs
Publsiher: World Scientific
Total Pages: 516
Release: 2007
ISBN 10: 981270695X
ISBN 13: 9789812706959
Language: EN, FR, DE, ES & NL

Biological Networks Book Review:

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.

Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis
Author: Grady Hanrahan
Publsiher: CRC Press
Total Pages: 214
Release: 2011-01-18
ISBN 10: 9781439812594
ISBN 13: 1439812594
Language: EN, FR, DE, ES & NL

Artificial Neural Networks in Biological and Environmental Analysis Book Review:

Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound impact in the elucidation of complex biological, chemical, and environmental processes. Artificial Neural Networks in Biological and Environmental Analysis provides an in-depth and timely perspective on the fundamental, technological, and applied aspects of computational neural networks. Presenting the basic principles of neural networks together with applications in the field, the book stimulates communication and partnership among scientists in fields as diverse as biology, chemistry, mathematics, medicine, and environmental science. This interdisciplinary discourse is essential not only for the success of independent and collaborative research and teaching programs, but also for the continued interest in the use of neural network tools in scientific inquiry. The book covers: A brief history of computational neural network models in relation to brain function Neural network operations, including neuron connectivity and layer arrangement Basic building blocks of model design, selection, and application from a statistical perspective Neurofuzzy systems, neuro-genetic systems, and neuro-fuzzy-genetic systems Function of neural networks in the study of complex natural processes Scientists deal with very complicated systems, much of the inner workings of which are frequently unknown to researchers. Using only simple, linear mathematical methods, information that is needed to truly understand natural systems may be lost. The development of new algorithms to model such processes is needed, and ANNs can play a major role. Balancing basic principles and diverse applications, this text introduces newcomers to the field and reviews recent developments of interest to active neural network practitioners.

Introduction to Biological Networks

Introduction to Biological Networks
Author: Alpan Raval,Animesh Ray
Publsiher: CRC Press
Total Pages: 335
Release: 2016-04-19
ISBN 10: 1420010360
ISBN 13: 9781420010367
Language: EN, FR, DE, ES & NL

Introduction to Biological Networks Book Review:

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

Biological Data Mining in Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks
Author: Li, Xiao-Li,Ng, See-Kiong
Publsiher: IGI Global
Total Pages: 450
Release: 2009-05-31
ISBN 10: 1605663999
ISBN 13: 9781605663999
Language: EN, FR, DE, ES & NL

Biological Data Mining in Protein Interaction Networks Book Review:

"The goal of this book is to disseminate research results and best practices from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics"--Provided by publisher.

Applied Statistics for Network Biology

Applied Statistics for Network Biology
Author: Matthias Dehmer,Frank Emmert-Streib,Armin Graber,Armindo Salvador
Publsiher: John Wiley & Sons
Total Pages: 478
Release: 2011-04-08
ISBN 10: 9783527638086
ISBN 13: 3527638083
Language: EN, FR, DE, ES & NL

Applied Statistics for Network Biology Book Review:

The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.

Plant Systems Biology

Plant Systems Biology
Author: Sacha Baginsky,Alisdair R. Fernie
Publsiher: Springer Science & Business Media
Total Pages: 358
Release: 2007-02-16
ISBN 10: 3764372613
ISBN 13: 9783764372613
Language: EN, FR, DE, ES & NL

Plant Systems Biology Book Review:

This volume aims to provide a timely view of the state-of-the-art in systems biology. The editors take the opportunity to define systems biology as they and the contributing authors see it, and this will lay the groundwork for future studies. The volume is well-suited to both students and researchers interested in the methods of systems biology. Although the focus is on plant systems biology, the proposed material could be suitably applied to any organism.

Network Science

Network Science
Author: Ted G. Lewis, PhD
Publsiher: John Wiley & Sons
Total Pages: 524
Release: 2011-09-20
ISBN 10: 1118211014
ISBN 13: 9781118211014
Language: EN, FR, DE, ES & NL

Network Science Book Review:

A comprehensive look at the emerging science of networks Network science helps you design faster, more resilient communication networks; revise infrastructure systems such as electrical power grids, telecommunications networks, and airline routes; model market dynamics; understand synchronization in biological systems; and analyze social interactions among people. This is the first book to take a comprehensive look at this emerging science. It examines the various kinds of networks (regular, random, small-world, influence, scale-free, and social) and applies network processes and behaviors to emergence, epidemics, synchrony, and risk. The book's uniqueness lies in its integration of concepts across computer science, biology, physics, social network analysis, economics, and marketing. The book is divided into easy-to-understand topical chapters and the presentation is augmented with clear illustrations, problems and answers, examples, applications, tutorials, and a discussion of related Java software. Chapters cover: Origins Graphs Regular Networks Random Networks Small-World Networks Scale-Free Networks Emergence Epidemics Synchrony Influence Networks Vulnerability Net Gain Biology This book offers a new understanding and interpretation of the field of network science. It is an indispensable resource for researchers, professionals, and technicians in engineering, computing, and biology. It also serves as a valuable textbook for advanced undergraduate and graduate courses in related fields of study.

Statistical and Machine Learning Approaches for Network Analysis

Statistical and Machine Learning Approaches for Network Analysis
Author: Matthias Dehmer,Subhash C. Basak
Publsiher: John Wiley & Sons
Total Pages: 344
Release: 2012-06-26
ISBN 10: 111834698X
ISBN 13: 9781118346983
Language: EN, FR, DE, ES & NL

Statistical and Machine Learning Approaches for Network Analysis Book Review:

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

Biological Networks and Pathway Analysis

Biological Networks and Pathway Analysis
Author: Tatiana V. Tatarinova,Yuri Nikolsky
Publsiher: Humana Press
Total Pages: 509
Release: 2017-08-29
ISBN 10: 9781493970254
ISBN 13: 1493970259
Language: EN, FR, DE, ES & NL

Biological Networks and Pathway Analysis Book Review:

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.