Smiles
Showing 10 of 10 projects
A deep learning toolkit for computational chemistry and drug design research with PyTorch backend.
An open-source Java library for cheminformatics and bioinformatics, providing algorithms for molecular representation, analysis, and data processing.
A collection of BERT-like transformer models pre-trained on chemical SMILES data for drug design and property prediction.
A sequence-to-sequence transformer model for predicting chemical reaction pathways (retrosynthesis) with uncertainty calibration.
Deep learning model using convolutional neural networks to predict drug-target binding affinity from protein sequences and compound SMILES.
A Python library for fast random access to chemical descriptors and molecule indices, optimized for machine learning workflows.
A Java library for converting IUPAC chemical names to molecular structures (SMILES, CML, InChI) with high accuracy.
A Julia toolkit for graph-based molecule modeling, cheminformatics analysis, and chemical structure manipulation.
A T5-based model for bidirectional translation between molecular structures (SMILES) and natural language descriptions.
A Python package for easy molecular docking with a curated dataset and benchmark tasks for drug discovery.
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