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008			220601s2015 sz | o |||| 0|eng d
020			_a9783031794568
024	7		_a10.1007/978-3-031-79456-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRM301.25 _b2015 EB
100	1		_aChen, Bin _d1983- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687718
245	1	0	_aSemantic Breakthrough in Drug Discovery _cby Bin Chen, Huijun Wang, Ying Ding, David Wild
250			_a1st edition 2015
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (CXXXIV, 10 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Semantics and Knowledge _x2691-2031
505	0		_aIntroduction -- Data Representation and Integration Using RDF -- Data Representation and Integration Using OWL -- Finding Complex Biological Relationships in PubMed Articles using Bio-LDA -- Integrated Semantic Approach for Systems Chemical Biology Knowledge Discovery -- Semantic Link Association Prediction -- Conclusions -- References -- Authors' Biographies .
520			_aThe current drug development paradigm---sometimes expressed as, ``One disease, one target, one drug''---is under question, as relatively few drugs have reached the market in the last two decades. Meanwhile, the research focus of drug discovery is being placed on the study of drug action on biological systems as a whole, rather than on individual components of such systems. The vast amount of biological information about genes and proteins and their modulation by small molecules is pushing drug discovery to its next critical steps, involving the integration of chemical knowledge with these biological databases. Systematic integration of these heterogeneous datasets and the provision of algorithms to mine the integrated datasets would enable investigation of the complex mechanisms of drug action; however, traditional approaches face challenges in the representation and integration of multi-scale datasets, and in the discovery of underlying knowledge in the integrated datasets. The Semantic Web, envisioned to enable machines to understand and respond to complex human requests and to retrieve relevant, yet distributed, data, has the potential to trigger system-level chemical-biological innovations. Chem2Bio2RDF is presented as an example of utilizing Semantic Web technologies to enable intelligent analyses for drug discovery.Table of Contents: Introduction / Data Representation and Integration Using RDF / Data Representation and Integration Using OWL / Finding Complex Biological Relationships in PubMed Articles using Bio-LDA / Integrated Semantic Approach for Systems Chemical Biology Knowledge Discovery / Semantic Link Association Prediction / Conclusions / References / Authors' Biographies .
988			_aSynthesis Collection of Technology_2015
650		7	_2embne _9139235 _aDrogas
650		7	_2embne _9163805 _aWeb semántica
650		7	_2embne _9162648 _aData mining
700	1		_aWang, Huijun _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687719
700	1		_aDing, Ying _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687720
700	1		_aWild, David _q(David J.) _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687721
776	0	8	_iPrinted edition: _z9783031794551
776	0	8	_iPrinted edition: _z9783031794575
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-79456-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _eb _zSI