[PDF] Analyzing Network Data In Biology And Medicine eBook

Author : Nataša Pržulj
Publisher : Cambridge University Press
Page : 647 pages
File Size : 37,79 MB
Release : 2019-03-28
Category : Science
ISBN : 1108386245

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The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.

Author : Matthias Dehmer
Publisher : John Wiley & Sons
Page : 364 pages
File Size : 41,16 MB
Release : 2016-12-12
Category : Medical
ISBN : 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.

Author : Nataša Pržulj
Publisher : Cambridge University Press
Page : 647 pages
File Size : 30,81 MB
Release : 2019-03-28
Category : Language Arts & Disciplines
ISBN : 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.

Author : Matthias Dehmer
Publisher :
Page : pages
File Size : 20,52 MB
Release : 2016
Category : NATURE
ISBN : 9783527694365

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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.

Author : Fabricio Alves Barbosa da Silva
Publisher : Springer Nature
Page : 381 pages
File Size : 29,96 MB
Release : 2020-10-03
Category : Computers
ISBN : 3030518620

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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.

Author : Joseph Loscalzo
Publisher : Harvard University Press
Page : 449 pages
File Size : 10,4 MB
Release : 2017-02-01
Category : Medical
ISBN : 0674436539

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Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. With contributions from leading experts, Network Medicine introduces this rapidly evolving field of research, which promises to revolutionize the diagnosis and treatment of human diseases.

Author : Byung-Jun Yoon
Publisher : Springer Nature
Page : 220 pages
File Size : 24,60 MB
Release : 2021-01-13
Category : Medical
ISBN : 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.

Author : Avi Ma'ayan
Publisher : Springer Science & Business Media
Page : 204 pages
File Size : 34,27 MB
Release : 2012-06-25
Category : Medical
ISBN : 9400743300

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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.

Author : Davide Bacciu
Publisher : World Scientific
Page : 333 pages
File Size : 46,45 MB
Release : 2022-01-17
Category : Computers
ISBN : 1800610955

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Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.