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Chloroquine

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Discovery of potential 1,3,5-Triazine compounds against strains of Plasmodium falciparum using supervised machine learning models.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The Malaria burden was an escalating global encumbrance and need to be addressed with critical care. Anti-malarial drug discovery was integrated with supervised machine learning (ML) models to identify potent thiazolyl-traizine derivatives. This assi...

Prediction of the inhibitory concentrations of chloroquine derivatives using deep neural networks models.

Journal of biomolecular structure & dynamics
In recent years, deep neural networks have begun to receive much attention, which has obvious advantages in feature extraction and modeling. However, in the using of deep neural networks for the QSAR modeling process, the selection of various paramet...

Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2.

European review for medical and pharmacological sciences
Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug s...

Toward a Coronavirus Knowledge Graph.

Genes
This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a col...

Scratch-AID, a deep learning-based system for automatic detection of mouse scratching behavior with high accuracy.

eLife
Mice are the most commonly used model animals for itch research and for development of anti-itch drugs. Most laboratories manually quantify mouse scratching behavior to assess itch intensity. This process is labor-intensive and limits large-scale gen...