Kalli Kappel

This paper introduces DAPTEV, an AI framework for designing aptamers targeting the SARS-CoV-2 spike protein, showing it can generate structurally complex aptamers with strong binding affinities.

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 paper presents RECCES-Rosetta, a computational framework that accurately predicts RNA nearest neighbor energy parameters, including non-standard nucleotides, with RMSD below 1 kcal/mol in blind tests.