Author

Michael Floßdorf

Technical University of Munich

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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Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Atefeh KazeroonianiD· 1 shared Beate Spießberger· 1 shared Christian SchulziD· 1 shared Daksh P.S. Pamar· 1 shared Diyuan LuiD· 1 shared Florent AilloudiD· 1 shared Markus GerhardiD· 1 shared Michael P. MendeniD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperMicrobiology

Atefeh KazeroonianORCID

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Author profile →

1 paper

Recent·Most cited

Decoding Helicobacter pylori Resistance: Machine Learning Enhanced Prediction of Antibiotic Susceptibility using Whole-Genome Sequencing

Florent Ailloud, Diyuan Lu, Beate Spießberger, Daksh P.S. Pamar, Atefeh Kazeroonian, Michael Floßdorf, Mónica Oleastro, Christian Schulz, Markus Gerhard, Michael P. Menden, Sebastian Suerbaum

This study uses machine learning to improve metronidazole resistance prediction in Helicobacter pylori using whole-genome sequencing, achieving better accuracy than traditional methods.

bioRxiv · Aug 7, 2025 · PreprintMicrobiology