Active learning enables evolutionary discovery and characterization of fungal transcriptional activators
A hybrid framework that leverages high-throughput molecular assays and active learning to quantify biological properties across evolutionary space and provides a general strategy for building predictive models that better capture the diversity of natural sequence-to-function relationships is presented.
Lucas M. Waldburger, Hunter M. Nisonoff, Marissa A. Zintel et al.
· Genome Biology · 0 citations