Buscar
Mostrando ítems 31-40 de 689
Foodinformatics: Quantitative Structure-Property Relationship Modeling of Volatile Organic Compounds in Peppers
(Wiley Blackwell Publishing, Inc, 2019-01)
The aim of this work was the foodinformatic (chemoinformatic) modeling of volatile organic compounds (VOCs) of different samples of peppers based on a quantitative structure-property relationship (QSPR) for the retention ...
Quantitative Structure-Property Relationship (QSPR) Studies of Alcoholic and Nonalcoholic Beverages, Including Wines, Beers, and Citrus Juices
(Elsevier, 2019)
Proteins are the basis of life, playing main roles in electron, oxygen,and metal transport, signaling and enzymatic activities, among others.Proteins and their block constituents, for example, amino acids,are provided from ...
Amino acid profiles and quantitative structure-property relationship models as markers for Merlot and Torrontés wines
(Elsevier, 2013-05)
Quantitative structure–property relationships (QSPRs) were applied to the aminograms obtained by HPLC in our laboratories for Torrontés and Merlot wines. Dragon theoretical descriptors were derived for a set of optimized ...
Predicting the bioconcentration factor through a conformation-independent QSPR study
(Taylor & Francis Ltd, 2017-09)
The ANTARES dataset is a large collection of known and verified experimental bioconcentrationfactor data, involving 851 highly heterogeneous compounds from which 159 of them arepesticides. In this Special Issue devoted to ...
A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system
(Universidade de São Paulo, Faculdade de Ciências Farmacêuticas, 2010)
Drugs acting on the central nervous system (CNS) have to cross the blood-brain barrier (BBB) in order to perform their pharmacological actions. Passive BBB diffusion can be partially expressed by the blood/brain partition ...
From chemical structure to quantitative polymer properties prediction through convolutional neural networks
(Elsevier, 2020-04)
In this work convolutional-fully connected neural networks were designed and trained to predict the glass transition temperature of polymers based only on their chemical structure. This approach has shown to successfully ...
Quantitative structure-property relationship analysis for the retention index of fragrance-like compounds on a polar stationary phase
(Elsevier Science, 2015-11)
A quantitative structure-property relationship (QSPR) was developed for modeling the retention index of 1184 flavor and fragrance compounds measured using a Carbowax 20M glass capillary gas chromatography column. The 4885 ...
Application of quantitative structure-property relationship analysis to estimate the vapor pressure of pesticides
(Academic Press Inc Elsevier Science, 2016-06)
The application of molecular descriptors in describing Quantitative Structure Property Relationships (QSPR) for the estimation of vapor pressure (VP) of pesticides is of ongoing interest. In this study, QSPR models were ...
Immobilized Artificial Membrane Chromatography: Quantitative Structure-Retention Relationships of Structurally Diverse Drugs
(American Chemical Society, 2003-11)
The Chromatographic capacity factors (log k′) for 32 structurally diverse drugs were determined by high performance liquid chromatography (HPLC) on a stationary phase composed of phospholipids, the socalled immobilized ...