Large Scale Mining of Molecular Fragments with Wildcards


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HOFER, Heiko, Christian BORGELT, Michael R. BERTHOLD, 2003. Large Scale Mining of Molecular Fragments with Wildcards. In: R. BERTHOLD, Michael, ed., Hans-Joachim LENZ, ed., Elizabeth BRADLEY, ed., Rudolf KRUSE, ed., Christian BORGELT, ed.. Advances in Intelligent Data Analysis V. Berlin, Heidelberg:Springer Berlin Heidelberg, pp. 376-385. ISBN 978-3-540-40813-0. Available under: doi: 10.1007/978-3-540-45231-7_35

@inproceedings{Hofer2003Large-5554, title={Large Scale Mining of Molecular Fragments with Wildcards}, year={2003}, doi={10.1007/978-3-540-45231-7_35}, number={2810}, isbn={978-3-540-40813-0}, address={Berlin, Heidelberg}, publisher={Springer Berlin Heidelberg}, series={Lecture Notes in Computer Science}, booktitle={Advances in Intelligent Data Analysis V}, pages={376--385}, editor={R. Berthold, Michael and Lenz, Hans-Joachim and Bradley, Elizabeth and Kruse, Rudolf and Borgelt, Christian}, author={Hofer, Heiko and Borgelt, Christian and Berthold, Michael R.} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:contributor>Berthold, Michael R.</dc:contributor> <dcterms:title>Large Scale Mining of Molecular Fragments with Wildcards</dcterms:title> <dcterms:issued>2003</dcterms:issued> <dc:rights>terms-of-use</dc:rights> <dspace:hasBitstream rdf:resource=""/> <dc:format>application/pdf</dc:format> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Hofer, Heiko</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <dc:language>eng</dc:language> <dcterms:abstract xml:lang="eng">The main task of drug discovery is to find novel bioactive molecules, i.e., chemical compounds that, for example, protect human cells against a virus. One way to support solving this task is to analyze a database of known and tested molecules with the aim to build a classifier that predicts whether a novel molecule will be active or inactive, so that future chemical tests can be focused on the most promising candidates. In [1] an algorithm for constructing such a classifier was proposed that uses molecular fragments to discriminate between active and inactive molecules. In this paper we present two extensions of this approach: A special treatment of rings and a method that finds fragments with wildcards based on chemical expert knowledge.</dcterms:abstract> <dcterms:available rdf:datatype="">2011-03-24T15:56:23Z</dcterms:available> <dc:contributor>Borgelt, Christian</dc:contributor> <dc:creator>Berthold, Michael R.</dc:creator> <dcterms:bibliographicCitation>First publ. in: Cryptographic Hardware and Embedded Systems. - Berlin: Springer, 2003, pp. 376-385</dcterms:bibliographicCitation> <dc:date rdf:datatype="">2011-03-24T15:56:23Z</dc:date> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:rights rdf:resource=""/> <dcterms:hasPart rdf:resource=""/> <dc:creator>Borgelt, Christian</dc:creator> <dc:contributor>Hofer, Heiko</dc:contributor> <bibo:uri rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> </rdf:Description> </rdf:RDF>

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