Sentence examples for using the quantitative structure from inspiring English sources
In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach.
In the present work, we have proposed a statistical model predicting the toxicity of ionic liquids (ILs) to Vibrio fischeri bacteria using the Quantitative Structure-Activity Relationships (QSAR) method.
With a focus on estimating antiwear properties of some heterocyclic additives, we use the quantitative structure tribo-ability relationship (QSTR) model to predict tribological data, which introduces the idea of computer-aided design into tribology.
Since 1991, the field of drug discovery has used the Quantitative Structure-Activity-Relationship (QSAR) approach in to optimize the drug leads [30].
Additional file 1: Figures S3 S4 and Additional file 1: Tables S3 S4 show the systematic analysis of the resulting community structures using the quantitative metrics proposed in the above section.
In this study, the structural requirements of penetration enhancers have been investigated using the Quantitative Structure Activity Relationship (QSAR) technique.
A 3D-QSPkR approach has been used to obtain the quantitative structure pharmacokinetic relationship for a series of quinolone drugs using SOMFA.
Although some chemical phenomena have been rationalized by establishing the quantitative structure-reactivity relationships using these reactivity indices in the gas phase [11], the presence of solvent is bound to affect the reactivity behaviors of chemical substances.
Here, we correlate kij to the pure component parameters of the Perturbed Chain – Statistical Associating Fluid Theory (PC-SAFT) EoS, using a Quantitative Structure Property Relationship (QSPR) model.
The theoretical results can be used to identify compounds with desired properties using quantitative structure activity relationship (QSAR) method [46].
Model parameters were obtained using quantitative structure property relationships (QSPRs) developed using multiple linear regression and artificial neural networks with Bayesian regularization.
