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Loscalzo, Joseph (ed.)

Network medicine : complex systems in human disease and therapeutics Joseph Loscalzo(ed.), Albert-László Barabási (ed.), Edwin K. Silverman (ed.) - Cambridge : Harvard University Press, ©2017 - xi, 436 p. : ill, ; 25 cm.

Includes index.

Scientific basis of network medicine / Edwin K. Silverman and Joseph Loscalzo -- Introduction to network analysis / Jorg Menche and Albert-Laszlo Barabasi -- Human interactomes in network medicine / Michael E. Cusick, Benoit Charloteaux, Thomas Rolland, Michael A. Calderwood, David E. Hill, and Marc Vidal -- Social networks in human disease / Martin W. Schoen and Douglas Luke -- Phenotype, pathophenotype and endo(patho)phenotype in network medicine / Calum A. MacRae -- A new paradigm for defining human disease and therapy / Joseph Loscalzo -- Complex disease genetics and network medicine / Edwin K. Silverman -- Transcriptomics and network medicine / Kimberly Glass and John Quackenbush -- 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, and I. Huvent -- Epigenetics and network medicine / Dawn L. DeMeo and Scott T. Weiss -- Metabolomics and network medicine / Jessica Lasky-Su and Clary B. Clish -- Using integrative Omics approaches in network medicine / Shuyi Ma, John C. Earls, James A. Eddy, and Nathan D. Price -- Cancer network medicine / Takeshi Hase, Samik Ghosh, Sucheendra K Palaniappan, and Hiroaki Kitano -- Systems pharmacology in network medicine / Edwin K. Silverman and Joseph Loscalzo -- Systems approaches to clinical trials / Elliott M. Antman -- Microbiomics in network medicine / Joanne E. Sordillo, George M. Weinstock, and Augusto A. Litonjua.

"Network medicine, a new field which developed from the application of systems biology approaches to human disease, embraces the complexity of multifactorial influences on disease, which can be driven by non-linear effects and molecular and statistical interactions.The development of comprehensive and affordable Omics platforms provides the data types for network medicine, and graph theory and statistical physics provide the theoretical framework to analyze networks. While network medicine provides a fundamentally different approach to understanding disease etiology, it will also lead to key differences in how diseases are treated--with multiple molecular targets that may require manipulation in a coordinated, dynamic fashion. Much remains to be learned regarding the optimal approaches to integrate different Omics data types and to perform network analyses; this book provides an overview of the progress that has been made and the challenges that remain."--

9780674436534

2016006644


Medical informatics.
Data integration (Computer science)
Diseases--Causes and theories of causation--Data processing.
Therapeutics--Data processing.

R858 / .N48 2017

610.285 / LOS-M

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