Fig. 1: Overview of the ProBound method.

A wide range of high-throughput experiments use selection on libraries of DNA, RNA or displayed protein molecules coupled with sequencing to characterize sequence-specific molecular interactions. ProBound uses machine learning tailored to model the recognition, selection and sequencing processes underlying these data to infer biophysically meaningful recognition models.