Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction
| Autor: | Alberto Manganaro, Giuseppina Gini, Dario Cattaneo, N. Golbamaki Bakhtyari, Thomas Ferrari, Emilio Benfenati |
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| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Quantitative structure–activity relationship
Safety Management Models Statistical Molecular Structure Process (engineering) Computer science Quantitative Structure-Activity Relationship Bioengineering General Medicine computer.software_genre Toxicology Knowledge extraction Drug Discovery Molecular Medicine Humans Data mining Organic Chemicals computer Mutagens |
| Popis: | This work proposes a new structure–activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence. |
| Databáze: | OpenAIRE |
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