Semantic Breakthrough in Drug Discovery (Record no. 85259)

000 -LEADER
fixed length control field 04364nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-3-031-79456-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164045.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2015 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031794568
-- 978-3-031-79456-8
082 04 - CLASSIFICATION NUMBER
Call Number 510
100 1# - AUTHOR NAME
Author Chen, Bin.
245 10 - TITLE STATEMENT
Title Semantic Breakthrough in Drug Discovery
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages CXXXIV, 10 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Data, Semantics, and Knowledge,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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 .
520 ## - SUMMARY, ETC.
Summary, etc The 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 .
700 1# - AUTHOR 2
Author 2 Wang, Huijun.
700 1# - AUTHOR 2
Author 2 Ding, Ying.
700 1# - AUTHOR 2
Author 2 Wild, David.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-79456-8
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Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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-- Mathematics.
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-- Internet programming.
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-- Application software.
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-- Computer networks .
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-- Ontology.
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-- Mathematics.
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-- Web Development.
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-- Computer and Information Systems Applications.
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-- Computer Communication Networks.
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-- Ontology.
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-- 2691-2031
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