GitHub - d-cole/Latent_5HT2A_binding_prediction: Models for prediction of 5HT2A binding affinity from SMILES

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Name	Name	Last commit message	Last commit date
Latest commit Daniel Added readme Jun 15, 2018 fab5ee6 · Jun 15, 2018 History 2 Commits
Ki_classifier.py	Ki_classifier.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
README.txt	README.txt	Added readme	Jun 15, 2018
encode_SMILEs.py	encode_SMILEs.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
explore_dataset.R	explore_dataset.R	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
ki_regression.py	ki_regression.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
pres_plots.py	pres_plots.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
processing_kiDB.py	processing_kiDB.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018
smile_to_encoding.py	smile_to_encoding.py	Initial Commit of molec latent binding affinity prediction	Jun 15, 2018

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Latent_5HT2A_binding_prediction

This repository contains .py and .R scripts for the preprocessing and training of models predicting 5HT2A receptor binding affinity from latent representations of SMILES.