000			03336cam a2200277 i 4500
999			_c51458 _d53005
003			ISURa
008			160209s2017 maua 001 0 eng c
020			_a9780674436534
020			_a0674436539
041			_aEnglish
082	0	0	_a610.285 _2NET
100			_aLoscalzo, Joseph, _eed _972619
245	0	0	_aNetwork medicine _bcomplex systems in human disease and therapeutics
260			_aCambridge _bMassachusetts : Harvard University Press _c2017
300			_axi, 436 p. _c25 cm.
500			_a 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
520			_a"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."--
650		0	_aMedical informatics. _972620
650		0	_aData integration (Computer science) _972621
650		0	_aDiseases _xCauses and theories of causation _xData processing. _972622
650		0	_aTherapeutics _xData processing. _972623
700	1		_aLoscalzo, Joseph, _eed _972619
700	1		_aBarabasi, Albert-Laszlo, _eed _972634
700	1		_aSilverman, Edwin K., _eed _972625
942			_2ddc _cLN