Molecular Fragment Mining for Drug Discovery

Cite This

Files in this item

Checksum: MD5:4ff400e770290d3d6643002a68463d06

BORGELT, Christian, Michael R. BERTHOLD, David E. PATTERSON, 2005. Molecular Fragment Mining for Drug Discovery. In: GODO, Lluís, ed.. Symbolic and Quantitative Approaches to Reasoning with Uncertainty. Berlin, Heidelberg:Springer Berlin Heidelberg, pp. 1002-1013. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84

@inproceedings{Borgelt2005Molec-24073, title={Molecular Fragment Mining for Drug Discovery}, year={2005}, doi={10.1007/11518655_84}, number={3571}, isbn={978-3-540-27326-4}, address={Berlin, Heidelberg}, publisher={Springer Berlin Heidelberg}, series={Lecture Notes in Computer Science}, booktitle={Symbolic and Quantitative Approaches to Reasoning with Uncertainty}, pages={1002--1013}, editor={Godo, Lluís}, author={Borgelt, Christian and Berthold, Michael R. and Patterson, David E.} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:creator>Borgelt, Christian</dc:creator> <dc:creator>Berthold, Michael R.</dc:creator> <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 in order to find structural properties of molecules that determine whether a molecule will be active or inactive, so that future chemical tests can be focused on the most promising candidates. A promising approach to this task was presented in [2]: an algorithm for finding molecular fragments that discriminate between active and inactive molecules. In this paper we review this approach as well as two extensions: a special treatment of rings and a method to find fragments with wildcards based on chemical expert knowledge.</dcterms:abstract> <dcterms:rights rdf:resource=""/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:bibliographicCitation>Symbolic and quantitative approaches to reasoning with uncertainty : 8th European Conference, ECSQARU 2005, Barcelona, Spain, July 6 - 8, 2005; proceedings / Lluís Godo (ed.). - Berlin [u.a.] : Springer, 2005. - S. 1002-1013. - (Lecture notes in computer science ; 3571 : Lecture notes in artificial intelligence). - ISBN 978-3-540-27326-4</dcterms:bibliographicCitation> <dc:contributor>Berthold, Michael R.</dc:contributor> <dc:language>eng</dc:language> <dspace:isPartOfCollection rdf:resource=""/> <dc:rights>terms-of-use</dc:rights> <dc:contributor>Patterson, David E.</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Patterson, David E.</dc:creator> <dcterms:issued>2005</dcterms:issued> <dcterms:hasPart rdf:resource=""/> <bibo:uri rdf:resource=""/> <dc:date rdf:datatype="">2013-07-26T07:23:49Z</dc:date> <dc:contributor>Borgelt, Christian</dc:contributor> <dcterms:isPartOf rdf:resource=""/> <dcterms:title>Molecular Fragment Mining for Drug Discovery</dcterms:title> <dspace:hasBitstream rdf:resource=""/> <dcterms:available rdf:datatype="">2013-07-26T07:23:49Z</dcterms:available> </rdf:Description> </rdf:RDF>

Downloads since Oct 1, 2014 (Information about access statistics)

Borgelt_240736.pdf 121

This item appears in the following Collection(s)

Search KOPS


My Account