Author

O. Dubuis

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· 3 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Assay:whole-genome sequencing· 2 Research Focus:clustering· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

A. Egli· 4 shared A. Buser· 2 shared A. Cuenod· 2 shared A. Zeller· 2 shared C. Saalfrank· 2 shared D. Lang· 2 shared H. M. Seth-Smith· 2 shared J. Hadfield· 2 shared

Activity by Year

2020-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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4 shared papersMicrobiology

A. Egli

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Ancient methicillin-resistant Staphylococcus aureus: expanding current knowledge using molecular epidemiological characterization of a Swiss legacy collection

V. Benvenga, A. Cuenod, S. Purushothaman, G. Dasen, M. Weisser, S. Bassetti, T. Roloff, M. Siegemund, U. Heininger, J. A. Bielicki, M. Wehrli, P. Friderich, R. Frei, A. Widmer, K. Herzog, , A. Egli

The paper characterizes ancient MRSA isolates from 1965-1987 and compares them to modern isolates, identifying novel sequence types and lineage dynamics.

bioRxiv · Apr 27, 2023 · PreprintMicrobiology

Direct Antimicrobial Resistance Prediction from clinical MALDI-TOF mass spectra using Machine Learning

C. Weis, A. Cuenod, B. Rieck, F. Llinares-Lopez, O. Dubuis, S. Graf, C. Lang, M. Oberle, M. Brackmann, K. K. Soegaard, M. Osthoff, K. Borgwardt, A. Egli

This study uses machine learning to predict antimicrobial resistance from MALDI-TOF mass spectra, achieving high AUROC values and showing potential to improve clinical treatment decisions.

bioRxiv · Jul 30, 2020Microbiology

Characterising the epidemic spread of Influenza A/H3N2 within a city through phylogenetics

N. F. Müller, D. Wüthrich, N. Goldman, N. Sailer, C. Saalfrank, M. Brunner, N. Augustin, H. M. Seth-Smith, Y. Hollenstein, M. Syedbasha, D. Lang, R. A. Neher, O. Dubuis, M. Naegele, A. Buser, , T. Stadler

The paper uses genetic sequence data and patient metadata to analyze local influenza transmission dynamics in Basel, Switzerland, finding that temperature trends correlate with transmission and that elderly and school children drive different transmission networks.

bioRxiv · Apr 27, 2020Evolutionary Biology

High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

A. Egli, N. Goldman, N. F. Müller, M. Brunner, D. Wuethrich, S. Tschudin-Sutter, E. Hodcroft, R. Neher, C. Saalfrank, J. Hadfield, T. Bedfors, M. Syedbasha, T. Vogel, N. Augustin, J. Bauer, , R. Schneider-Sliwa

This study maps influenza transmission in a city at high resolution, finding socioeconomic factors like income influence infection patterns and vaccination rates, independent of population density.

bioRxiv · Apr 3, 2020 · PreprintMicrobiology