Inga Jarmoskaite

The paper develops a CRISPR-based mutagenesis approach combined with machine learning to model cis-regulatory features of ADAR-mediated RNA editing, explaining over 70% of editing level variation.

The paper quantitatively tests RNA secondary structure prediction algorithms using RNA-MaP, revealing significant deviations between predictions and experimental stabilities.

This study explains off-target activity in RNA-guided nucleases through kinetic models, offering a framework for improving their specificity.