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020 _a9783031794568
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024 7 _a10.1007/978-3-031-79456-8
_2doi
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082 0 4 _a510
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100 1 _aChen, Bin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981843
245 1 0 _aSemantic Breakthrough in Drug Discovery
_h[electronic resource] /
_cby Bin Chen, Huijun Wang, Ying Ding, David Wild.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aCXXXIV, 10 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _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 .
650 0 _aMathematics.
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650 0 _aInternet programming.
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650 0 _aApplication software.
_981844
650 0 _aComputer networks .
_931572
650 0 _aOntology.
_95277
650 1 4 _aMathematics.
_911584
650 2 4 _aWeb Development.
_935505
650 2 4 _aComputer and Information Systems Applications.
_981845
650 2 4 _aComputer Communication Networks.
_981846
650 2 4 _aOntology.
_95277
700 1 _aWang, Huijun.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981847
700 1 _aDing, Ying.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981848
700 1 _aWild, David.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981849
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031794551
776 0 8 _iPrinted edition:
_z9783031794575
830 0 _aSynthesis Lectures on Data, Semantics, and Knowledge,
_x2691-2031
_981851
856 4 0 _uhttps://doi.org/10.1007/978-3-031-79456-8
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