Author

Maria Fyta

RWTH Aachen UniversityORCID 0000-0002-5425-7907Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Bioengineering· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Assay:long-read sequencing· 2 Approach:statistical model· 2 Approach:graph neural network· 1 Organism:human· 1 Research Focus:imputation· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Jan Claas BehrendsiD· 2 shared Mayukh KansariiD· 2 shared Tobias EnssleniD· 2 shared Alexander SpeckiD· 1 shared Chandan Kumar DasiD· 1 shared Chih‐Yuan LiniD· 1 shared Hanna SimoniD· 1 shared Jan HübbersiD· 1 shared

Activity by Year

2026-2026 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersBioinformatics

Jan Claas BehrendsORCID

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4 papers

Recent·Most cited

Benchmarking Imputation Methods for Single-Cell RNA Sequencing Data Using Peripheral Blood Mononuclear Cells from Acute Myocardial Infarction Patients

Ramesh Prathiksha, Maria Fyta

The paper benchmarks imputation methods on scRNA-seq data from AMI patients to assess their impact on downstream analysis.

bioRxiv · Aug 27, 2026 · PreprintBioinformatics

Nanopore event detection in a simple and adaptive way

Peijia Wei, Mayukh Kansari, Michael Mierzejewski, Tobias Ensslen, Chih‐Yuan Lin, Kyril Kavetsky, Peter D. Jones, Jan Claas Behrends, Marija Drndić, Maria Fyta

This paper introduces a simple, fast, and adaptable cluster-based event detection algorithm for nanopore signals, showing improved efficiency and reduced noise in biological nanopore data.

bioRxiv · May 11, 2026 · PreprintBioinformatics

Graph-based learning and read-out of nanopore translocation event signals

Mayukh Kansari, Tobias Ensslen, Jan Claas Behrends, Maria Fyta

This paper develops a graph-based framework for label-free detection of nanopore translocation events, showing it can predict event morphology across a range of voltages.

bioRxiv · Apr 30, 2026 · PreprintBioengineering

AlphaFold 3 captures oligomeric states and interaction dynamics of MLO ion channels

Jan Hübbers, Chandan Kumar Das, Alexander Speck, Myriam Elisabeth Fuerst, Hanna Simon, Marie Laufens, Sophie Levecque, Matthias Freh, Maria Fyta, Ralph Panstruga

This paper uses AlphaFold 3 to predict MLO protein structures, revealing their oligomeric states, pore dynamics, and interactions with calcium sensors and exocyst subunits.

bioRxiv · Apr 13, 2026 · PreprintPlant Biology