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| Author | : Nataša Pržulj |
| Publisher | : Cambridge University Press |
| Total Pages | : 647 |
| Release | : 2019-03-28 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 1108432239 |
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 | : Nataša Pržulj |
| Publisher | : Cambridge University Press |
| Total Pages | : 647 |
| Release | : 2019-03-28 |
| Genre | : Science |
| ISBN | : 1108386245 |
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 |
| Total Pages | : 364 |
| Release | : 2016-12-12 |
| Genre | : Medical |
| ISBN | : 3527339582 |
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 | : Matthias Dehmer |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : NATURE |
| ISBN | : 9783527694365 |
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 | : José Luis Oliveira |
| Publisher | : Springer |
| Total Pages | : 413 |
| Release | : 2005-10-24 |
| Genre | : Medical |
| ISBN | : 3540316582 |
| Author | : Joseph Loscalzo |
| Publisher | : Harvard University Press |
| Total Pages | : 449 |
| Release | : 2017-02-01 |
| Genre | : Medical |
| ISBN | : 0674436539 |
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 | : Steve Horvath |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 433 |
| Release | : 2011-04-30 |
| Genre | : Science |
| ISBN | : 144198819X |
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.
| Author | : Byung-Jun Yoon |
| Publisher | : Springer Nature |
| Total Pages | : 220 |
| Release | : 2021-01-13 |
| Genre | : Medical |
| ISBN | : 3030571734 |
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 |
| Total Pages | : 204 |
| Release | : 2012-06-25 |
| Genre | : Medical |
| ISBN | : 9400743300 |
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 | : Fabricio Alves Barbosa da Silva |
| Publisher | : Springer Nature |
| Total Pages | : 381 |
| Release | : 2020-10-03 |
| Genre | : Computers |
| ISBN | : 3030518620 |
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.
