Our paper describing the pyRBDome pipeline now on BioRXiv!
Liang-Cui, Niki and Hugh, together with many honour and MSc students, spent the last three years building a powerful pipeline for identifying RNA-binding residues in putative RNA-binding proteins.
We have used the pipeline to study hundreds of human and Staphylococcus aureus proteins. Using our analysis methods, we also developed a new machine learning model that enhances the prediction of RNA-binding amino acids within proteins. Our method will enable users to increase the confidence in high-throughput detection of RNA-binding proteins and RNA-binding regions within proteins.
The paper can be found at the following link: