Author

Olga V. Kalinina

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Open access Jul 2026

Interpretable prediction of DNA replication origins in S. cerevisiae using DNABERT and DNABERT-2

This study fine-tune two genome-based pretrained language models, DNABERT and DNABERT-2, to predict replication origins in budding yeast and unravel the DNA base composition behind them, and demonstrates that both models identify replication origin sequences, albeit through different learning strategies.

Zohreh Piroozeh, I. Akerman, Olga V. Kalinina et al. · BMC Bioinformatics · 0 citations

#machine learning Preprint Aug 2026

Task- and dataset-specific information in protein language models

Protein language models (PLMs) have transferred the latest advances from natural language processing to computational biology. These models, trained on large corpora of protein sequence data, are widely used to translate amino acid sequences into latent-space embeddings, ready for use in diverse downstream tasks (DTs)....

R. Joeres, Ilya S. Senatorov, A. Kolchina et al. · 0 citations