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Molecular Transformer is an open-source sequence-to-sequence Transformer model (OpenNMT-py) for data-driven chemical reaction prediction and retrosynthesis planning. Trained on USPTO reaction datasets
Use with AI
Install the MCP server or CLI to instantly fetch Moleculartransformers documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/moleculartransformers
GraphCast is Google DeepMind's graph neural network for skillful medium-range global weather forecasting. It predicts 10-day forecasts of hundreds of atmospheric variables at 0.25° resolution (~25 km)
1 shared topic • 2 shared operations
ChemProp — directed message passing neural network (D-MPNN) for molecular property prediction from SMILES. Train classification, regression, or multiclass models with atom/bond featurization, scaffold
2 shared topics
GRITS Toolbox is a free, open-source desktop application for processing, annotating, and archiving glycomics mass spectrometry data. It automates MS/MS spectral annotation of glycan fragments against
2 shared topics
Uni-Mol universal 3D molecular representation learning framework for molecular property prediction, protein-ligand docking, drug-target interaction, and binding affinity scoring. Covers unimol_tools P
2 shared topics
Bambi (BAyesian Model-Building Interface) is a high-level Python package for fitting Bayesian generalized linear and generalized linear mixed models using a concise, R-style Wilkinson formula syntax.
1 shared topic • 1 shared operation