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A QSTR-based expert system to predict sweetness of molecules
ArticleAbstract: This work describes a novel approach based on advanced molecular similarity to predict the sweetnessPalabras claves:classification, Expert System, Molecular descriptors, QSAR, SweetnessAutores:Ballabio D., Consonni V., Cristian Rojas Villa, Grisoni F., Mauri A., Piercosimo Tripaldi, Rojas C., Todeschini R.Fuentes:googlescopusClassification-based QSAR models for the prediction of the bioactivity of ACE-inhibitor peptides
ArticleAbstract: Background: Local classification models were used to establish Quantitative Struc-ture−Activity RelaPalabras claves:ACE, Bioactive peptides, Dragon descriptors, Knn, N3, QSARAutores:Andres PEREZ-GONZALEZ, Ballabio D., Johann Radax, Piercosimo Tripaldi, Rojas C., Todeschini R.Fuentes:scopusQuantitative structure–activity relationships to predict sweet and non-sweet tastes
ArticleAbstract: The aim of this work was the calibration and validation of mathematical models based on a quantitatiPalabras claves:classification, K-NEAREST NEIGHBORS, QSAR, SweetnessAutores:Ballabio D., Consonni V., Cristian Rojas Villa, Mauri A., Piercosimo Tripaldi, Rojas C., Todeschini R.Fuentes:googlescopus