Tadeusz Satława

RIOT annotates immunoglobulin sequences by handling nucleotide and amino acid data, using an open germline database, and improving speed and accuracy over existing tools.

The paper introduces nanoBERT, a transformer model for predicting amino acids in nanobody sequences, showing its advantage over general models and gene-specific statistics.

The paper shows that pre-training deep learning models on physically accurate antibody structures improves the prediction of physically plausible CDR-H3 loop geometries.