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http://repositorio.ufla.br/jspui/handle/1/41417| Título: | On the use of PLS and N-PLS in MIA-QSAR: Azole antifungals |
| Palavras-chave: | MIA-QSAR PLS regression N-PLS regression Antifungals Multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) Partial least squares regression Multiway partial least squares regression |
| Data do documento: | Mar-2009 |
| Editor: | Elsevier |
| Citação: | GOODARZI, M.; FREITAS, M. P. On the use of PLS and N-PLS in MIA-QSAR: Azole antifungals. Chemometrics and Intelligent Laboratory Systems, [S.l.], v. 96, n. 1, p. 59-62, Mar. 2009. DOI: 10.1016/j.chemolab.2008.11.007. |
| Resumo: | The antifungal activities of a series of azole derivatives have been modeled by using MIA (multivariate image analysis) descriptors. Two regression methods were applied to correlate such descriptors with the activities column vector: bilinear (classical) and multilinear (N-way) partial least squares - PLS and N-PLS, respectively. The PLS-based model for this series of compounds demonstrated higher predictive ability than the N-PLS-based model, in opposition to some published results for other series of compounds. The activities block was taken in logarithmic scale (pMIC90(cpd)/pMIC90(bifonazole)) and the statistical performance of both models was found to be significantly better than the CoMFA analysis previously established. |
| URI: | https://www.sciencedirect.com/science/article/abs/pii/S0169743908002104 http://repositorio.ufla.br/jspui/handle/1/41417 |
| Aparece nas coleções: | DQI - Artigos publicados em periódicos |
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