Nicolas Goedert

A Systematic Benchmark of Machine Learning Methods for Protein-RNA Interaction Prediction

This study benchmarks 11 machine learning methods for predicting in vivo RBP-RNA interactions across hundreds of CLIP-seq datasets and RBPs.

Towards In-Silico CLIP-seq: Predicting Protein-RNA Interaction via Sequence-to-Signal Learning

RBPNet predicts CLIP crosslink count distributions from RNA sequences, outperforming existing methods and enabling variant impact scoring.