Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution
q-bio.QM, cs.AI, cs.LG
Submitted: 2026-10-06
Updated: 2026-10-06
Related papers
- A likelihood-based framework for simultaneously learning both noise and growth dynamics using biologically-informed neural networks
- Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions
- Resolving satellite-in situ mismatches in Net Primary Production using high-frequency in situ bio-optical observations in the subpolar Northwest Atlantic
- easyplater: The easy way to generate microplate designs deconvolved from multivariate clinical data
- Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Bayesian Uncertainty Quantification
- OmniBioTwin: A System-of-Twinned-Systems Framework for Health Digital Twins