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.
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.
LLM-inspired BiLSTM pipeline for real-time, multi-label toxicity inference across adversarial discourse modalities.
Dataset used in Tox24 challenge
Data accompanying Tox24 Challenge manuscript
Comparison of methods for toxicity prediction from SMILEs
AI-powered pharmacogenomics platform using GATv2 to predict organ health, drug interactions, and personalized longevity insights from DNA, lifestyle, and medications.
🛡️ Open-source moderation powered by AI
A Polymer Toxicity Prediction Tool using PSMILE Strings
Scaffold-aware GCN with attention-based substructure pooling for multi-task Tox21 toxicity prediction. 12-task model with scaffold-split evaluation achieving 0.789 AUC-ROC on best assay.
Lightweight ML model for predicting SR-MMP toxicity from SMILES.
A possible framework for detecting and explaining toxicity in intimate Italian textual conversations.
The prediction_script will enable you to predict whether your query protein sequence is cardiotoxic, neurotoxic, and/or enterotoxic.
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