QSARtuna: QSAR model building with the optuna framework
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Updated
Oct 25, 2024 - Jupyter Notebook
QSARtuna: QSAR model building with the optuna framework
Physicochemical properties, indices and descriptors for amino-acid sequences.
Exploring QSAR Models for Activity-Cliff Prediction
Active learning workflow to train and fine-tune target molecular property predictors with chemist feedback in goal-oriented molecule generation.
This workflow includes Quantitative Structure-Activity Relationship (QSAR) models to predict the hERG-related cardiotoxicity of chemicals.
Code for paper
Quantitative structure activity relationship models (QSAR models) using 6 molecular descriptors of 908 chemicals to predict quantitative acute aquatic toxicity (LC50 value) towards the fish Pimephales promelas (fathead minnow).
A modular inverse QSAR pipeline
Open Source, machine learning QSAR model with public data or your local data, The model utilises molecular descriptors as the independent variable, bioactivity as the dependent variable, random forest as a mathematical model.
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)
Research project predicting monomer pair reactivity ratios with QSAR models based on the U-V scheme and quantum chemical descriptors.
Estimate maximum performance bounds based on experimental errors for ML datasets
Exploring QSAR: From Data Collection to Structure-Activity Relationship Analysis
Linear regression model using gradient descent algorithm for weight estimation of QSAR Biodegradation
Code used in the elective course Advanced Computational Methods in Drug Discovery: AI and Physics-Based Simulations at Leiden University.
C. Tong List of Selected Publications & Abstracts
Predicting biodegradability using QSAR models with K-Nearest Neighbors, Decision Tree, Neural Network, Logistic Regression
MCDCalc: Calculation of Markov Singular Values Molecular Descriptors Online Tool
Developing a regression-based QSAR (quantitative structure-activity relationships) model to identify compounds that have 3-chymotrypsin-like protease (3CLpro) inhibitory activity.
A one stop destination of open source tools in Computer Aided Drug Design (CADD)
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