| Autor: |
Wilton DJ; Department of Information Studies, University of Sheffield, Sheffield S10 2TN, UK., Harrison RF, Willett P, Delaney J, Lawson K, Mullier G |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of chemical information and modeling [J Chem Inf Model] 2006 Mar-Apr; Vol. 46 (2), pp. 471-7. |
| DOI: |
10.1021/ci050397w |
| Abstrakt: |
This paper discusses the use of binary kernel discrimination (BKD) for identifying potential active compounds in lead-discovery programs. BKD was compared with established virtual screening methods in a series of experiments using pesticide data from the Syngenta corporate database. It was found to be superior to methods based on similarity searching and substructural analysis but inferior to a support vector machine. Similar conclusions resulted from application of the methods to a pesticide data set for which categorical activity data were available. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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