Dmitriy Umerenkov

The paper uses G4-DNABERT to map G-quadruplexes to enhancer and promoter regions, supporting their role in chromatin looping and gene regulation.

The paper identifies Z-flipon variants' roles in health and disease by analyzing Z-DNA and Z-RNA effects across multiple genomic features and disease associations.

PROSTATA predicts protein stability changes from point mutations using a transformer-based model, outperforming existing neural network approaches.

SEMA predicts conformational B-cell epitopes using transfer learning on antigen sequences and structures, achieving ROC AUC of 0.76 on an independent test set.