Title |
Mining basic active structures from a large-scale database
|
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Published in |
Journal of Cheminformatics, March 2013
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DOI | 10.1186/1758-2946-5-15 |
Pubmed ID | |
Authors |
Naoto Takada, Norihito Ohmori, Takashi Okada |
Abstract |
The Pubchem Database is a large-scale resource for chemical information, containing millions of chemical compound activities derived by high-throughput screening (HTS). The ability to extract characteristic substructures from such enormous amounts of data is steadily growing in importance. Compounds with shared basic active structures (BASs) exhibiting G-protein coupled receptor (GPCR) activity and repeated dose toxicity have been mined from small datasets. However, the mining process employed was not applicable to large datasets owing to a large imbalance between the numbers of active and inactive compounds. In most datasets, one active compound will appear for every 1000 inactive compounds. Most mining techniques work well only when these numbers are similar. |
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Mendeley readers
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