Network Medicine: Complex Systems in Human Disease and Therapeutics
Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases. With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesis of the progress being made and the challenges that remain.

Medical researchers have long sought to identify single molecular defects that cause diseases, with the goal of developing silver-bullet therapies to treat them. But this paradigm overlooks the inherent complexity of human diseases and has often led to treatments that are inadequate or fraught with adverse side effects. Rather than trying to force disease pathogenesis into a reductionist model, network medicine embraces the complexity of multiple influences on disease and relies on many different types of networks: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression in biological samples. The authors offer a systematic approach to understanding complex diseases while explaining network medicine’s unique features, including the application of modern genomics technologies, biostatistics and bioinformatics, and dynamic systems analysis of complex molecular networks in an integrative context.

By developing techniques and technologies that comprehensively assess genetic variation, cellular metabolism, and protein function, network medicine is opening up new vistas for uncovering causes and identifying cures of disease.

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Network Medicine: Complex Systems in Human Disease and Therapeutics
Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases. With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesis of the progress being made and the challenges that remain.

Medical researchers have long sought to identify single molecular defects that cause diseases, with the goal of developing silver-bullet therapies to treat them. But this paradigm overlooks the inherent complexity of human diseases and has often led to treatments that are inadequate or fraught with adverse side effects. Rather than trying to force disease pathogenesis into a reductionist model, network medicine embraces the complexity of multiple influences on disease and relies on many different types of networks: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression in biological samples. The authors offer a systematic approach to understanding complex diseases while explaining network medicine’s unique features, including the application of modern genomics technologies, biostatistics and bioinformatics, and dynamic systems analysis of complex molecular networks in an integrative context.

By developing techniques and technologies that comprehensively assess genetic variation, cellular metabolism, and protein function, network medicine is opening up new vistas for uncovering causes and identifying cures of disease.

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Overview

Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases. With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesis of the progress being made and the challenges that remain.

Medical researchers have long sought to identify single molecular defects that cause diseases, with the goal of developing silver-bullet therapies to treat them. But this paradigm overlooks the inherent complexity of human diseases and has often led to treatments that are inadequate or fraught with adverse side effects. Rather than trying to force disease pathogenesis into a reductionist model, network medicine embraces the complexity of multiple influences on disease and relies on many different types of networks: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression in biological samples. The authors offer a systematic approach to understanding complex diseases while explaining network medicine’s unique features, including the application of modern genomics technologies, biostatistics and bioinformatics, and dynamic systems analysis of complex molecular networks in an integrative context.

By developing techniques and technologies that comprehensively assess genetic variation, cellular metabolism, and protein function, network medicine is opening up new vistas for uncovering causes and identifying cures of disease.


Product Details

ISBN-13: 9780674436534
Publisher: Harvard University Press
Publication date: 02/01/2017
Pages: 448
Product dimensions: 6.10(w) x 9.40(h) x 1.30(d)

About the Author

Joseph Loscalzo is Chair of the Department of Medicine and Physician-in-Chief, Brigham and Women’s Hospital, and Hersey Professor of the Theory and Practice of Medicine, Harvard Medical School.

Albert-László Barabási is Robert Gray Dodge Professor of Network Science and Director of the Center for Complex Network Research at Northeastern University.

Edwin K. Silverman is Chief of the Channing Division of Network Medicine at Brigham and Women’s Hospital and Professor of Medicine at Harvard Medical School.

Nathan Price is Chief Science Officer of Thorne HealthTech and Professor at the Institute for Systems Biology. Selected as an Emerging Leader in Health and Medicine by the National Academy of Medicine, he received the Grace A. Goldsmith Award for his work on scientific wellness and has coauthored over 200 peer-reviewed scientific publications.

Table of Contents

Preface Joseph Loscalzo Albert-László Barabási Edwin K. Silverman ix

1 Scientific Basis of Network Medicine Edwin K. Silverman Joseph Loscalzo 1

2 Introduction to Network Analysis Jörg Menche Albert-László Barabási 17

3 Human Interactomes in Network Medicine Michael E. Cusick Benoit Charloteaux Thomas Rolland Michael A. Calderwood David E. Hill Marc Vidal 44

4 Social Networks in Human Disease Douglas A. Luke Martin W. Schoen 89

5 Phenotype, Pathophenotype, and Endo(patho)phenotype in Network Medicine Calum A. MacRae 112

6 A New Paradigm for Denning Human Disease and Therapy Joseph Loscalzo 137

7 Complex Disease Genetics and Network Medicine Edwin K. Silverman 153

8 Transcriptomics and Network Medicine John Quackenbush Kimberly Glass 177

9 Post-translational Modifications of the Proteome: The Example of Tau in the Neuron and the Brain Guy Lippens Jeremy Gunawardena Isabelle Landrieu Caroline Smet-Nocca Sudhakaran Prabakaran Benjamin Parent Arnaud Leroy Isabelle Huvent 198

10 Epigenetics and Network Medicine Dawn L. DeMeo Scott T. Weiss 224

11 Metabolomics and Network Medicine Jessica Lasky-Su Clary B. Clish 238

12 Using Integrative-omics Approaches in Network Medicine Shuyi Ma John C. Earls James A. Eddy Nathan D. Price 267

13 Cancer Network Medicine Takeshi Hase Samik Ghosh Sucheendra K. Palaniappan Hiroaki Kitano 294

14 Systems Pharmacology in Network Medicine Edwin K. Silverman Joseph Loscalzo 324

15 Systems Approaches to Clinical Trials Elliott M. Antman 341

16 Microbiomics in Network Medicine Joanne E. Sordillo George M. Weinstock Augusto A. Litonjua 371

Abbreviations 407

Glossary 411

Contributors 423

Index 427

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