Carlos Oliver

Ribo-LENS detects RNA small-molecule binding sites using a geometric deep-learning framework, outperforming existing methods and enabling efficient virtual screening.

The paper introduces a motif mining approach to identify higher-order biomarkers from expression data, showing improved performance in classification and clustering compared to traditional methods in a COVID-19 study.

RNAmigos2 improves RNA virtual screening by combining semi-supervised graph learning and large-scale docking data, achieving high accuracy and speed.

OptiMol optimizes molecular binding affinities using a hybrid structure- and ligand-based approach, improving docking scores and compound generation efficiency.

RNAmigos predicts small molecule ligands for RNA binding sites using augmented base pairing networks, showing improved performance over baselines and highlighting the importance of non-canonical base pairs.

The paper introduces BayesPairing 2, a sequence search algorithm for RNA 3D module identification, showing improved speed and accuracy over its predecessor.