Trippe, Brian L.

Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,369

De novo design of protein structure and function with RFdiffusion

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,325

Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem

Trippe, B. L., Yim, J., Tischer, D., Baker, D., Broderick, T., Barzilay, R., & Jaakkola, T. (2022) · arXiv

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 92