Author

Zuzanna Karwowska

Jagiellonian UniversityORCID 0000-0002-4673-4697Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Research Focus:clustering· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Tomasz KościółekiD· 4 shared Aleksander ByrskiiD· 1 shared Anastasia RomanchenkoiD· 1 shared Elin OrgiD· 1 shared Ewa SzczurekiD· 1 shared Jan MajtaiD· 1 shared Kaja MilanowskaiD· 1 shared Krzysztof OdrzywołekiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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4 shared papersBioinformatics

Tomasz KościółekORCID

Mutual co-authors in cluster

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4 papers

Recent·Most cited

A universal taxonomic and functional human gut microbiome model for disease classification and phenotype discovery

Zuzanna Karwowska, Marcin Możejko, Wojciech Nowak, Anastasia Romanchenko, Ewa Szczurek, Tomasz Kościółek

This paper introduces GUT-FORMer, a transformer-based autoencoder for gut microbiome analysis, achieving accurate disease classification and host trait prediction.

bioRxiv · May 5, 2026 · PreprintBioinformatics

Microbiome time series data reveal predictable patterns of change

Zuzanna Karwowska, Paweł Szczerbiak, Tomasz Kościółek

This study analyzes microbiome time series data to show that the gut microbiome is stable and predictable over time despite individual bacterial volatility.

Microbiology Spectrum · Aug 20, 2024Peer-reviewedBioinformatics

Effects of Data Transformation and Model Selection on Feature Importance in Microbiome Classification Data

Zuzanna Karwowska, Oliver Aasmets, Tomasz Kościółek, Elin Org

This study evaluates how data transformations and model selection affect feature importance in microbiome classification, showing that presence-absence transformations perform well and only a small subset of features is critical for classification.

bioRxiv · Sep 19, 2023 · PreprintBioinformatics

Deep embeddings to comprehend and visualize microbiome protein space

Krzysztof Odrzywołek, Zuzanna Karwowska, Jan Majta, Aleksander Byrski, Kaja Milanowska, Tomasz Kościółek

The paper uses a deep learning model to represent microbial proteins for alignment-free analysis and visualization, showing it can capture structural and functional features.

Scientific Reports · Jun 20, 2022Peer-reviewedBioinformatics