Property guidance for protein sequence generative models with ProteinGuide - @jlistgarten.bsky.social @savagecatsonly.bsky.social www.nature.com/articles/s41...
Property guidance for protein sequence generative models with ProteinGuide - Nature Biotechnology
On-the-fly conditioning of pretrained protein generative models guides protein generation toward specific properties.
nature.com
Our ProteinGuide paper is finally out! Thanks to all the co-authors @junhaobearxiong.bsky.social, @ishangaur.bsky.social, @hnisonoff.bsky.social, @loltrogge.bsky.social, @jlistgarten.bsky.social, @savagecatsonly.bsky.social! @innovativegenomics.bsky.social www.nature.com/articles/s41...
Property guidance for protein sequence generative models with ProteinGuide - Nature Biotechnology
On-the-fly conditioning of pretrained protein generative models guides protein generation toward specific properties.
nature.com
Our review on AI for protein engineering is out now, about this too-fast-moving field full of hype and overclaim, yet one that is having a real impact on the world and can be described in a coherent manner without histrionics. www.science.org/eprint/666XR...
How artificial intelligence is reengineering protein engineering
Over the past decades, protein engineering has matured into a field of its own, driven by computational modeling and high-throughput wet lab experiments, with broad application in therapeutics, diagnostics, agriculture, and manufacturing. In recent years,...
science.org
Hunter Nisonoff and Junhao Xiong are at ICLR presenting their poster on how to correctly do guidance for diffusion and FM in discrete state spaces, such as for protein engineering (joint w Stephan Allenspach). Go chat with them! iclr.cc/virtual/2025...
ICLR Poster Unlocking Guidance for Discrete State-Space Diffusion and Flow ModelsICLR 2025
iclr.cc