De novo prediction of RNA-protein interactions with Graph Neural Networks

Abstract

AbstractRNA-binding proteins (RBPs) are key co- and post-transcriptional regulators of gene expression, playing a crucial role in many biological processes. Experimental methods like CLIP-seq have enabled the identification of transcriptome-wide RNA-protein interactions for select proteins, however the time and resource intensive nature of these technologies call for the development of computational methods to complement their predictions. RNA-binding proteins (RBPs) are key co- and post-transcriptional regulators of gene expression, playing a crucial role in many biological processes. Experimental methods like CLIP-seq have enabled the identification of transcriptome-wide RNA-protein interactions for select proteins, however the time and resource intensive nature of these technologies call for the development of computational methods to complement their predictions.