K. H. Johansen

Exploring noise in TCR specificity data through supervised learning

Specificity-driven protein binder design with Odin-Multi

Odin-Multi is presented, a binder design framework that optimises a shared binder sequence against several complexes simultaneously, applying attractive objectives to on-targets and repulsive objectives to off-targets, and widens the range of binding behaviours accessible to computational design.

Hybrid quantum-classical de novo design of MHC-binding peptides

Deep generative models have become a leading approach for designing therapeutic molecules, yet efficiently exploring vast biomolecular sequence spaces remains difficult, particularly for targets with limited training data. The prior distribution that seeds a generative model shapes which regions of sequence space it ex...