Molecular Fragment Mining for Drug Discovery

Borgelt, Christian; Berthold, Michael R.; Patterson, David E.

Molecular Fragment Mining for Drug Discovery

Dateien

Borgelt_240736.pdfGröße: 310.18 KBDownloads: 218

Datum

2005

Autor:innen

Borgelt, Christian

Berthold, Michael R.

Patterson, David E.

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen 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_84

Zusammenfassung

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.

Fachgebiet (DDC)

004 Informatik

Zitieren

ISO 690

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, 2005, pp. 1002-1013. Lecture Notes in Computer Science. 3571. ISBN 978-3-540-27326-4. Available under: doi: 10.1007/11518655_84

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.}
}

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