Chemical representation learning paper in Digital Discovery
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Updated
May 22, 2024 - Jupyter Notebook
Chemical representation learning paper in Digital Discovery
A simple tool to predict the general toxicity and calculate the synthesize accessibility (SA) score for small molecules.
Official repository for multitask deep learning models.
NLP deep learning model for multilingual toxicity detection in text 📚
An improved method for predicting toxicity of the peptides and designing of non-toxic peptides
Toxformer is an attempt at using transformers to predict the toxicity of molecules from their molecular structure using the T3DB database.
some scripts using deepchem
Dataset used in Tox24 challenge
The prediction_script will enable you to predict whether your query protein sequence is cardiotoxic, neurotoxic, and/or enterotoxic.
This is a Pytorch implementation of the paper: Application of Self-Supervised Graph Transformers for Developing Classification Models for Tox21 Bioactivity and Regression Models to Predict Inhalation Toxicity Lethal Concentrations
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