Author

Frank Fleischmann

Center for Molecular Fingerprinting

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Biophysics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Mihaela ŽigmaniD· 2 shared Tarek EissaiD· 2 shared Annette PetersiD· 1 shared Barbara Maria Obermayer-PietschiD· 1 shared Birgit LinkohriD· 1 shared Csilla Lakatos· 1 shared Diana DebreceniiD· 1 shared Domokos GerőiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBiophysics

Mihaela ŽigmanORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Individuality and information content of infrared molecular profiles: insights from a large longitudinal health-profiling study

Zita I. Zarandy, Flora B. Nemeth, Tarek Eissa, Csilla Lakatos, Dora Nagy, Diana Debreceni, Frank Fleischmann, Zoltán Kovács, Domokos Gerő, Mihaela Žigman, Ferenc Krausz, Kosmas V. Kepesidis

This study compares the individuality and information content of infrared molecular profiles with clinical laboratory data in a longitudinal cohort, finding infrared profiles more informative for individual identification.

bioRxiv · Apr 13, 2026 · PreprintBiophysics

CODI: Enhancing machine learning-based molecular profiling through contextual out-of-distribution integration

Tarek Eissa, Marinus Huber, Barbara Maria Obermayer-Pietsch, Birgit Linkohr, Annette Peters, Frank Fleischmann, Mihaela Žigman

CODI improves ML model generalization by integrating synthetic out-of-distribution data into molecular fingerprint datasets, enhancing classification accuracy in longitudinal clinical studies.

PNAS Nexus · Oct 1, 2024Peer-reviewedBioinformatics