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Details for article 4 of 7 found articles
| Title: |
Large scale mining of molecular fragments with wildcards |
| Author: |
Heiko Hofer Christian Borgelt Michael R. Berthold |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 8 (2004) nr. 5 pages 495-504 |
| Year: |
2004-10-29 |
| Contents: |
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. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 4 of 7 found articles
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