Chemical representation learning paper in Digital Discovery
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Updated
May 22, 2024 - Jupyter Notebook
Chemical representation learning paper in Digital Discovery
MolEnc: a molecular encoder using rdkit and OCaml.
A modular inverse QSAR pipeline
Estimate maximum performance bounds based on experimental errors for ML datasets
👨🔬 A command-line application that utilizes the RDKit library to compute molecular descriptors and fingerprints, aiding in the analysis and characterization of chemical structures
Code for the paper Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
QSARtuna: QSAR model building with the optuna framework
🧪DrugHunter - a web-based application for predicting the pharmacological activity of new drugs
A tool for creating Quantitative Structure Property Relationship (QSPR) models.
Automated QSAR based on multiple small molecule descriptors
Evaluation Framework for AI-driven Molecular Design of Multi-target Drugs
Modeling framework for eTRANSAFE project
Descriptive analysis and QSAR modelling for tox_21 datasets
drugdesign.org source of truth
A new python package to visualize molecules in dots hover
Supplementary repository to the publication "Hybrid machine learning and experimental studies of antiviral potential of ionic liquids against P100, MS2, and Phi6"
A package to perform fingerprints from spectroscopy datas.
A cheminformatics package to perform Applicability Domain of molecular fingerprints based in similarity calculation.
An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
QSAR Bioactivity Predictor is a Python application that allows users to create QSAR models to predict bioactivity for a specific target.
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