Browsing by Journal "J. Chem. Inf. Model."

Showing items 1-4 of 4

Liu, S.; Cai, S.; Cao, C.; Li, Z. Molecular Electronegative Distance Vector (MEDV) Related to 15 Properties of Alkanes. J. Chem. Inf. Model. 2000, 40, 6, 1337–1348.

Published: Geven Piir (2014-10-30)

Abstract: Several quantitative structure−property relationship (QSPR) models between 15 basic physical properties or thermodynamic functions of alkanes and their molecular electronegative distance vectors (MEDV) are developed. For six of the properties boiling point (BP), density (D) at 25 °C, refraction index (RI) at 25 °C, critical temperature (CT), critical pressure ...

PhysChem Regression
Oja, M.; Sild, S.; Maran, U. Logistic Classification Models for pH-Permeability Profile: Predicting Permeability Classes for the Biopharmaceutical Classification System. J. Chem. Inf. Model. 2019, 59, 2442-2455.

Published: Mare Oja, Sulev Sild, Uko Maran (2019-02-21)

Abstract: Permeability is used to describe and evaluate the absorption of drug substances in the human gastrointestinal tract (GIT). Permeability is largely dependent on fluctuating pH that causes the ionization of drug substances and also influences regional absorption in the GIT. Therefore, classification models that characterize permeability at wide range of pH-s ...

Toxicokinetics Classification DescriptorCalculation
Papa, E.; Villa, F.; Gramatica, P. Statistically Validated QSARs, Based on Theoretical Descriptors, for Modeling Aquatic Toxicity of Organic Chemicals in Pimephales promelas (Fathead Minnow). J. Chem. Inf. Model. 2005, 45, 5, 1256–1266.

Published: Iiris Kahn (2014-04-08)

Abstract: The use of Quantitative Structure?Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)96h in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new ...

EcoTox Regression QMRF
Tetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure-Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Model. 1999, 39, 491-507.

Published: Priit Ahte (2015-05-28)

Abstract: Radial basis function (RBF) neural network models for the simultaneous estimation of flash point (Tf) and boiling point (Tb) based on 25 molecular functional groups and their first-order molecular connectivity index (1χ) have been developed. The success of the whole modeling process depended on a network optimization strategy based on biharmonic spline ...

PhysChem Regression

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