The interest in the application of machine learning techniques (MLT) as drug design tools is
growing in the last decades. The reason for this is related to the fact that the drug design is …

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily are responsible for the
metabolism of many drugs, environmental chemicals and endogenous compounds …

The objective of this study is to compare the predictive ability of Bayesian regularization with
Levenberg–Marquardt Artificial Neural Networks. To examine the best architecture of neural …

The characteristics of the OPLS method have been investigated for the purpose of
discriminant analysis (OPLS‐DA). We demonstrate how class‐orthogonal variation can be …

Patients with Liver disease have been continuously increasing because of excessive
consumption of alcohol, inhale of harmful gases, intake of contaminated food, pickles and …

Background In the study of associations between genomic data and complex phenotypes
there may be relationships that are not amenable to parametric statistical modeling. Such …

Drug toxicity is frequently caused by electrophilic reactive metabolites that covalently bind to
proteins. Epoxides comprise a large class of three-membered cyclic ethers. These …

The objective of this study was to predict the irrigated and rainfed wheat output energy with
three soft computing models include Artificial Neural Network (MLP and RBF models) and …

The Support Vector Machine (SVM) is an algorithm that derives a model used for the
classification of data into two categories and which has good generalization properties. This …

Interest in reducing eructed CH 4 is growing, but measuring CH 4 emissions is expensive
and difficult in large populations. In this study, we investigated the effectiveness of milk mid …