Recent advances in the machine learning-based drug-target interaction prediction
W Zhang, W Lin, D Zhang, S Wang… - Current drug …, 2019 - ingentaconnect.com
Background: The identification of drug-target interactions is a crucial issue in drug discovery.
In recent years, researchers have made great efforts on the drug-target interaction …
In recent years, researchers have made great efforts on the drug-target interaction …
Data curation can improve the prediction accuracy of metabolic intrinsic clearance
T Esaki, R Watanabe, H Kawashima… - Molecular …, 2019 - Wiley Online Library
A key consideration at the screening stages of drug discovery is in vitro metabolic stability,
often measured in human liver microsomes. Computational prediction models can be built …
often measured in human liver microsomes. Computational prediction models can be built …
ToxicBlend: virtual screening of toxic compounds with ensemble predictors
Timely assessment of compound toxicity is one of the biggest challenges facing the
pharmaceutical industry today. A significant proportion of compounds identified as potential …
pharmaceutical industry today. A significant proportion of compounds identified as potential …
[PDF][PDF] Supplementary Material: DeepTox: Toxicity Prediction using Deep Learning
A Mayr, G ünter Klambauer, T Unterthiner… - … Learning methods for …, 2019 - epub.jku.at
The Supplementary Material contains additional information on the chemical descriptors
(Section 1), how the Tox21 challenge dataset can be augmented (Section 2), how …
(Section 1), how the Tox21 challenge dataset can be augmented (Section 2), how …