1 code implementation • 20 Dec 2022 • Patrick Emami, Aidan Perreault, Jeffrey Law, David Biagioni, Peter C. St. John
We introduce a sampling framework for evolving proteins in silico that supports mixing and matching a variety of unsupervised models, such as protein language models, and supervised models that predict protein function from sequence.
1 code implementation • 26 Jul 2018 • Peter C. St. John, Caleb Phillips, Travis W. Kemper, A. Nolan Wilson, Michael F. Crowley, Mark R. Nimlos, Ross E. Larsen
We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets.
BIG-bench Machine Learning Vocal Bursts Intensity Prediction