Protein Engineering seminars
January 2026
Design of new protein functions using deep learning
David Baker· University of Washington; Howard Hughes Medical Institute, USA
Recorded
David Baker presents recent advances in designing proteins for functions that natural evolution has not been required to solve. The approach begins with a desired structure or activity and uses deep learning to propose amino acid sequences expected to realise it. The resulting designs are translated into synthetic genes, produced as proteins and tested experimentally. The lecture connects computational design with laboratory characterisation, explaining how the combination can create new molecular functions relevant to medicine, technology and sustainability. Its focus is the construction and evaluation of proteins from scratch, extending the protein-design research recognised by the 2024 chemistry prize.
Video · 59 min · CaptionsStructural BiologyMachine LearningSeries: Paul G. Allen School of Computer Science & Engineering, University of Washington
January 2023
Engineering an inhibitor-resistant human CSF1R variant for microglia replacement
Terhi Lohela· University of Helsinki
Recorded
October 2022
Minimal genetically encoded tags for fluorescent protein labeling in living neurons
Aleksandra Arsic· Werner Reichardt Centre for Integrative Neuroscience (CIN), Tübingen University
Thu, Oct 20 · 16:00 UTC · Online
December 2020
Mechanical properties of our unstable protein building blocks
Nancy Forde· Simon Fraser University
Fri, Dec 11 · 05:00 UTC
July 2020
Deep learning for protein design
Lucy Colwell· Google Research - Cambridge UK
Wed, Jul 29 · 03:45 UTC · Online
End of results.