I will described a nonparametric framework for locally adaptive signal processing and analysis. This framework is based upon the notion of Kernel Regression which we generalize to adapt to local characteristics of the given data, resulting in descriptors which take into account both the spatial density of the samples (”the geometry”), and the actual values of those samples (”the radiometry”). T...

binary logistic regression (blr) has been developed as non-linear models to establish quantitative structure- activity relationships (qsar) between structural descriptors and biochemical activity of carbonic anhydrase inhibitors. using a training set consisted of 21 compounds with known ki values, the model was trained and tested to solve two-class problems as active or inactive on the basis of...

It is important to determine whether a candidate molecule is capable of penetrating the plasma-brain barrier indrug discovery and development. The aim of this paper is to establish a predictive model for plasma-brainbarrier penetration using simple descriptors The usefulness of the quantum chemical descriptors, calculated atthe level of the DFT and HE theories using 6-310* basis set for QSAR st...

In this work, quantitative structure-property relationship (QSPR) approaches were used to predict the redox potential of 42 phenolic antioxidants. The structures of all compounds optimized by the AM1 semi-empirical method and then a large number of molecular descriptors were calculated for each compound in the data set. Subsequently, stepwise multilinear regression was applied to select the mos...