Molecular Fragment Mining for Drug Discovery

Kurzanzeige
dc.contributor.authorBorgelt, Christian
dc.contributor.authorBerthold, Michael R.
dc.contributor.authorPatterson, David E.deu
dc.date.accessioned2013-07-26T07:23:49Zdeu
dc.date.available2013-07-26T07:23:49Zdeu
dc.date.issued2005
dc.description.abstractThe 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.eng
dc.description.versionpublished
dc.identifier.citationSymbolic 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 978-3-540-27326-4deu
dc.identifier.doi10.1007/11518655_84deu
dc.identifier.ppn391514342deu
dc.identifier.urihttp://kops.uni-konstanz.de/handle/123456789/24073
dc.language.isoengdeu
dc.legacy.dateIssued2013-07-26deu
dc.rightsterms-of-usedeu
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/deu
dc.subject.ddc004deu
dc.titleMolecular Fragment Mining for Drug Discoveryeng
dc.typeINPROCEEDINGSdeu
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kops.citation.bibtex
@inproceedings{Borgelt2005Molec-24073,
  year={2005},
  doi={10.1007/11518655_84},
  title={Molecular Fragment Mining for Drug Discovery},
  number={3571},
  isbn={978-3-540-27326-4},
  publisher={Springer Berlin Heidelberg},
  address={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.}
}
kops.citation.iso690BORGELT, 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, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84deu
kops.citation.iso690BORGELT, 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, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84eng
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kops.sourcefieldGODO, Lluís, ed.. <i>Symbolic and Quantitative Approaches to Reasoning with Uncertainty</i>. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84deu
kops.sourcefield.plainGODO, Lluís, ed.. Symbolic and Quantitative Approaches to Reasoning with Uncertainty. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84deu
kops.sourcefield.plainGODO, Lluís, ed.. Symbolic and Quantitative Approaches to Reasoning with Uncertainty. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84eng
kops.submitter.emailchristoph.petzmann@uni-konstanz.dedeu
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relation.isAuthorOfPublication56ea9ab6-14a4-493e-8ef1-3c064e0c50a1
relation.isAuthorOfPublication.latestForDiscoveryf3246f9d-f7ef-459f-9b0a-4ffd7be08597
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source.publisherSpringer Berlin Heidelberg
source.publisher.locationBerlin, Heidelberg
source.relation.ispartofseriesLecture Notes in Computer Science
source.titleSymbolic and Quantitative Approaches to Reasoning with Uncertainty

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