Floris J. van der Flier

This paper introduces a probabilistic preferential learning model for variant effect prediction, showing that uncertainty-aware strategies improve acquisition performance on single-mutation datasets.

This study evaluates whether electrostatic representations improve variant effect prediction models using DMS data, but finds no advantage over evolutionary models.

The paper shows that structural features of enzymes influence the predictability of variant effects, with consistent dependencies across multiple models.