DGL-LifeSci

ProteinMPNN — deep learning-based protein sequence design from backbone structures. Uses message passing neural networks to predict amino acid sequences that fold into a given 3D backbone. Supports fi

2 shared topics • 2 shared operations

DeepChem — Python framework for deep learning in drug discovery, materials science, quantum chemistry, and biology. Provides molecular featurizers (ECFP, graph convolutions, Coulomb matrices), pre-bui

2 shared topics • 1 shared operation

GNNExplainer explains predictions made by graph neural networks by learning sparse masks over subgraph structure and node features. Use for post-hoc GNN interpretability, identifying important edges a

2 shared topics • 1 shared operation

Prosit — deep learning framework for predicting MS2 fragment ion spectra and indexed retention times (iRT) from peptide sequences. Enables in silico spectral library generation for any organism and pr

2 shared topics • 1 shared operation

Boltz-1 — open-source deep learning model for predicting biomolecular 3D structures and interactions, approaching AlphaFold3-level accuracy. Supports protein, DNA, RNA, and small-molecule ligand struc

1 shared topic • 2 shared operations