Bryan Bryson — accepted AI-conference papers

2026

SwitchCraft: Programmatic Design of State-Switching Proteins

Bowen Jing, Mihir Bafna, Anisha Parsan, Heyuan Ni, David Kwabi-Addo, Bryan Bryson +2

ICML 2026poster

Multistate mechanisms underlie many of the complex functions observed in natural proteins. The ability to rationally design multistate proteins would have transformative implications for many areas of biotechnology, yet lies beyond the capabilities of existing deep learning frameworks for protein de…

Cited by 0 Source ↗Scholar ↗

2020

Learning Mutational Semantics

Brian Hie, Ellen Zhong, Bryan Bryson, Bonnie Berger

NeurIPS 2020poster

In many natural domains, changing a small part of an entity can transform its semantics; for example, a single word change can alter the meaning of a sentence, or a single amino acid change can mutate a viral protein to escape antiviral treatment or immunity. Although identifying such mutations can…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗