"Drug Activity Prediction" · 3 results

Implementation of Multiple-Instance Learning in Drug Activity Prediction

Fu, Gang2019

In the context of drug discovery and development, much effort has been exerted to determine which conformers of a given molecule are responsible for the observed biological activity. In this work we aimed to predict bioactive conformers using a variant of supervised learning, named …

mississippi Repository record for Implementation of Multiple-Instance Learning in Drug Activity Prediction (opens in a new tab)

Random Forests Based Rule Learning And Feature Elimination

Liu, Sheng2019

… for good interpretation while preserving the prediction performance. We propose an efficient approach, combining rule extraction and feature elimination, based on 1-norm regularized random forests. This approach simultaneously extracts a small number of rules generated by random forests and …

mississippi Repository record for Random Forests Based Rule Learning And Feature Elimination (opens in a new tab)

Discovery of Novel Glycogen Synthase Kinase-3beta Inhibitors: Molecular Modeling, Virtual Screening, and Biological Evaluation

Fu, Gang2020

… neurodegenerative disease. Recent advances in drug discovery targeting GSK-3 involved extensive computational modeling techniques. Both ligand/structure-based approaches have been well explored to design ATP-competitive inhibitors. Molecular modeling plus dynamics simulations can provide …

mississippi Repository record for Discovery of Novel Glycogen Synthase Kinase-3beta Inhibitors: Molecular Modeling, Virtual Screening, and Biological Evaluation (opens in a new tab)

Global ETD Search

Results

Implementation of Multiple-Instance Learning in Drug Activity Prediction

Random Forests Based Rule Learning And Feature Elimination

Discovery of Novel Glycogen Synthase Kinase-3beta Inhibitors: Molecular Modeling, Virtual Screening, and Biological Evaluation