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Campo DC | Valor | Idioma |
---|---|---|
dc.creator | Freitas, Matheus P. | - |
dc.date.accessioned | 2020-06-14T22:56:45Z | - |
dc.date.available | 2020-06-14T22:56:45Z | - |
dc.date.issued | 2009-01 | - |
dc.identifier.citation | FREITAS, M. P. MIA-QSTR study of different organic compounds to Pimephales promelas. Medicinal Chemistry Research, [S.l.], v. 18, p. 648-655, Jan. 2009. | pt_BR |
dc.identifier.uri | https://link.springer.com/article/10.1007/s00044-008-9156-6 | pt_BR |
dc.identifier.uri | http://repositorio.ufla.br/jspui/handle/1/41416 | - |
dc.description.abstract | A quantitative structure–toxicity relationship (QSTR) model based on multivariate image analysis was built to predict the toxicity of 30 organic compounds against fathead minnow (Pimephales promelas), a fish species of wide occurrence. The derived multivariate image analysis (MIA) applied to QSTR (MIA-QSTR) model provided good correlation between chemical structure and toxicity, i.e., r 2 of 0.96, q 2 of 0.59, and q220%q20%2 of 0.61 – the squared correlation coefficients of the linear regression of experimental versus predicted 50% lethal concentration (LC50) plots for the calibration, leave-one-out,and leave-20%-out cross-validation, respectively. The method demonstrated the potential to be used as a tool for prediction of toxicity data in vertebrate animals. | pt_BR |
dc.language | en_US | pt_BR |
dc.publisher | Springer | pt_BR |
dc.rights | restrictAccess | pt_BR |
dc.source | Medicinal Chemistry Research (MCRE) | pt_BR |
dc.subject | MIA-QSTR | pt_BR |
dc.subject | Organic compounds | pt_BR |
dc.subject | Phimephales promelas | pt_BR |
dc.subject | Toxicity | pt_BR |
dc.subject | Multivariate image analysis through quantitative structure toxicity relation (MIA-QSTR) | pt_BR |
dc.subject | Multivariate image analysis (MIA) | pt_BR |
dc.subject | Quantitative structure toxicity relationship (QSTR) | pt_BR |
dc.title | MIA-QSTR study of different organic compounds to Pimephales promelas | pt_BR |
dc.type | Artigo | pt_BR |
Aparece nas coleções: | DQI - Artigos publicados em periódicos |
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