HDAC-isoform-selectivity-ML-models

This repository contains necessary files for ML models to predict selectivity of compounds against HDAC1 and HDAC6

Requirements

jupyter, scikit-learn, numpy, pandas, rdkit
For generation of MAP4 fingerprints, install the package by Reymound Group (https://github.com/reymond-group/map4)
For testing of available, install LazyPredict library (https://pypi.org/project/lazypredict/)
For optimization of hyperparameters, install Optuna software (https://optuna.readthedocs.io/en/stable/)

Name		Name	Last commit message	Last commit date
Latest commit History 157 Commits
BioactivityModels		BioactivityModels
CompareSelectivityPredictions		CompareSelectivityPredictions
SelectivityModels		SelectivityModels
Additioal File 2 - External Dataset.csv		Additioal File 2 - External Dataset.csv
Additional File 1 - Datasets.csv		Additional File 1 - Datasets.csv
FP.py		FP.py
Fingerprint_generation.ipynb		Fingerprint_generation.ipynb
LazyPredict_classification.ipynb		LazyPredict_classification.ipynb
README.md		README.md
map4.py		map4.py