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Large scale mining of molecular fragments with wildcards

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2004

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Intelligent Data Analysis. 2004, 8(5), pp. 495-504. ISSN 1088-467X. eISSN 1571-4128

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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.

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ISO 690HOFER, Heiko, Christian BORGELT, Michael R. BERTHOLD, 2004. Large scale mining of molecular fragments with wildcards. In: Intelligent Data Analysis. 2004, 8(5), pp. 495-504. ISSN 1088-467X. eISSN 1571-4128
BibTex
@article{Hofer2004Large-5517,
  year={2004},
  title={Large scale mining of molecular fragments with wildcards},
  number={5},
  volume={8},
  issn={1088-467X},
  journal={Intelligent Data Analysis},
  pages={495--504},
  author={Hofer, Heiko and Borgelt, Christian and Berthold, Michael R.}
}
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