Chemical representation learning paper in Digital Discovery
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May 22, 2024 - Jupyter Notebook
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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.
An improved method for predicting toxicity of the peptides and designing of non-toxic peptides
Official repository for multitask deep learning models.
NLP deep learning model for multilingual toxicity detection in text 📚
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
OECD Test Guidelines-based toxicity prediction using machine learning. Comprehensive computational toxicology framework with pre-trained models for genotoxicity, carcinogenicity, acute toxicity, DART, and ecotoxicity endpoints.
Dataset used in Tox24 challenge
LLM-inspired BiLSTM pipeline for real-time, multi-label toxicity inference across adversarial discourse modalities.
Comparison of methods for toxicity prediction from SMILEs
A Polymer Toxicity Prediction Tool using PSMILE Strings
The prediction_script will enable you to predict whether your query protein sequence is cardiotoxic, neurotoxic, and/or enterotoxic.
pDILI_v1 is a python package that allows users to predict the association of drug-induced liver injury of a small molecule (1 = RISKy, 0 = Non-RISKy) and also visualize the molecule.
Lightweight ML model for predicting SR-MMP toxicity from SMILES.
🛡️ Open-source moderation powered by AI
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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