Author

Adriana Bukala

University of Warsaw

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Organism:bacteria (other)· 1 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:protein design· 1

Frequent Co-Authors

Anna GambiniD· 1 shared Christian L. MülleriD· 1 shared Ewa SzczurekiD· 1 shared Jacek SrokaiD· 1 shared Jan LudwiczakiD· 1 shared Jure BorišekiD· 1 shared Kamil Kamiński· 1 shared Krzysztof SzczepaniakiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Anna GambinORCID

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2 papers

Recent·Most cited

BATTLE-AMP: Benchmarking Antimicrobial Peptide Predictors

Paulina Szymczak, Adriana Bukala, Wojciech Zarzecki, Michal Šála, Jure Borišek, Setareh Fadavi, Roberto Olayo-Alarcón, Jacek Sroka, Maria Colomé‐Tatché, Anna Gambin, Christian L. Müller, Piotr Setny, Ewa Szczurek

BATTLE-AMP benchmarks antimicrobial peptide predictors using MIC data, showing that models trained on MIC data outperform binary classifiers and highlighting limitations in distinguishing active from inactive peptides.

bioRxiv · Jun 24, 2026 · PreprintBioinformatics

Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann-fold proteins

Kamil Kamiński, Jan Ludwiczak, Maciej Jasiński, Adriana Bukala, Rafał Madaj, Krzysztof Szczepaniak, Stanisław Dunin-Horkawicz

This paper develops deep learning models to predict and design cofactor specificity in Rossmann-fold proteins, achieving nearly perfect accuracy in benchmark tests.

Briefings in Bioinformatics · Sep 8, 2021Peer-reviewedBioinformatics