You're currently viewing an old version of this dataset. To see the current version, click here.

EIGENFOLD: Generative Protein Structure Prediction with Diffusion Models

Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational ensembles and flexibility that underlie biological function.

Data and Resources

Cite this as

Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi Jaakkola (2024). Dataset: EIGENFOLD: Generative Protein Structure Prediction with Diffusion Models. https://doi.org/10.57702/1ecoau7s

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2304.02198
Author Bowen Jing
More Authors
Ezra Erives
Peter Pao-Huang
Gabriele Corso
Bonnie Berger
Tommi Jaakkola
Homepage https://github.com/bjing2016/EigenFold