Mechanistic QSAR models for key human health endpoints
Wrapper to leverage cheminformatics tasks within scikit-learn workflows
QSAR Bioactivity Predictor is a Python application that allows users to create QSAR models to predict bioactivity for a specific target.
R implementation of QSAR (Quantitative Structure-Activity Realtionship) trees to predict the bioconcentration of chemical compounds.
Training data for "Prediction of clinically relevant drug-induced liver injury from structure using machine learning" (Hammann et al., J Appl Toxicol . 2019 Mar;39(3):412-419)
A machine learning app to assess the aggregation potential of Small Colloidally-Aggregating Molecules (SCAMS).
self learning and reference material on QSAR moleculear modelling
ProtMetrics is a library to compute molecular descriptors that can be used for QSAR and machine learning modeling.
QSAR models and data used for MAO-A and MAO-B virtual screening.
Reference implementation of the Vanishing Ranking Kernels (VRK) method
This project identifies potential EGFR inhibitors using a KNIME-based ML workflow and FBDD to discover key active fragments for lead optimization.
Pioneering Next-Generation AI for Scientific Breakthroughs. Starting with a JAK2 pIC50 Prediction Model.
Classify acetylcholinesterase inhibitor with LightGBM
Conjuntos de dados públicos dos diversos trabalhos do LACC.
Some thoughts on building QSARModeling in Rust.
Prediction of partition coefficient
Supplementary repository to the publication "Hybrid machine learning and experimental studies of antiviral potential of ionic liquids against P100, MS2, and Phi6"
Learning material derived from studies using the book 'Three Dimensional QSAR: Applications in Pharmacology and Toxicology (QSAR in Environmental and Health Sciences)'
SENDQSAR package enables researchers to build QSAR models from SEND datasets through streamlined data preprocessing, organ-wise toxicity scoring, descriptor calculation, and machine learning integration. The package supports automated workflows for model development and includes tools for visualization and performance evaluation.
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