Machine learning techniques and drug design
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 …
growing in the last decades. The reason for this is related to the fact that the drug design is …
In vitro–in vivo correlation for drugs and other compounds eliminated by glucuronidation in humans: pitfalls and promises
JO Miners, KM Knights, JB Houston… - Biochemical …, 2006 - Elsevier
Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily are responsible for the
metabolism of many drugs, environmental chemicals and endogenous compounds …
metabolism of many drugs, environmental chemicals and endogenous compounds …
Predictive abilities of Bayesian regularization and Levenberg–Marquardt algorithms in artificial neural networks: a comparative empirical study on social data
M Kayri - Mathematical and Computational Applications, 2016 - mdpi.com
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 …
Levenberg–Marquardt Artificial Neural Networks. To examine the best architecture of neural …
OPLS discriminant analysis: combining the strengths of PLS‐DA and SIMCA classification
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 …
discriminant analysis (OPLS‐DA). We demonstrate how class‐orthogonal variation can be …
Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat
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 …
there may be relationships that are not amenable to parametric statistical modeling. Such …
Modeling epoxidation of drug-like molecules with a deep machine learning network
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 …
proteins. Epoxides comprise a large class of three-membered cyclic ethers. These …
Assessment of energy consumption and modeling of output energy for wheat production by neural network (MLP and RBF) and Gaussian process regression (GPR) …
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 …
three soft computing models include Artificial Neural Network (MLP and RBF models) and …
Virtual screening of molecular databases using a support vector machine
RN Jorissen, MK Gilson - Journal of chemical information and …, 2005 - ACS Publications
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 …
classification of data into two categories and which has good generalization properties. This …
Predicting human drug glucuronidation parameters: application of in vitro and in silico modeling approaches
Cytochrome P450 (CYP) and UDP-glucuronosyltransferase (UGT), which both exist as
enzyme “superfamilies,” are together responsible for the metabolism of most hepatically …
enzyme “superfamilies,” are together responsible for the metabolism of most hepatically …
[HTML][HTML] Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via …
S Shadpour, TCS Chud, D Hailemariam… - Journal of Dairy …, 2022 - Elsevier
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 …
and difficult in large populations. In this study, we investigated the effectiveness of milk mid …