PyGVAMP
Graph VAMPNet Analysis of Molecular Dynamics Trajectories
Explore conformational states, transition kinetics, and residue-level interactions identified by PyGVAMP — a PyTorch Geometric implementation of GraphVAMPNets delivering up to 50x speedup over the original.
What is PyGVAMP
Interactive Reports
Explore 3D embeddings, protein structures, transition matrices, and attention patterns in fully interactive analysis pages.
Graph Neural Networks
Built on PyTorch Geometric, PyGVAMP constructs molecular graphs and learns state representations through neural message-passing.
Open Source
PyGVAMP is open source and actively developed. Check out the code, contribute, or use it for your own MD trajectory analysis.
Latest Analyses
Explore interactive reports generated by PyGVAMP from published MD trajectory datasets.