Author

Kathrin Schröder

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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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:E. coli· 1 Organism:human· 1 Assay:long-read sequencing· 1 Assay:metagenomics· 1 Organism:mouse· 1

Frequent Co-Authors

Albert PerlasiD· 1 shared Constanza B. VenegasiD· 1 shared Edward J MartiniD· 1 shared Ela SauerborniD· 1 shared Enrique RayoiD· 1 shared Hanna MartiiD· 1 shared Harika ÜreliD· 1 shared James M. FergusoniD· 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 paperBioinformatics

Albert PerlasORCID

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Author profile →

1 paper

Recent·Most cited

Nanopore- and AI-empowered microbial viability inference

Harika Ürel, Sabrina Benassou, Hanna Marti, Tim Reska, Ela Sauerborn, Yuri Pinheiro Alves de Souza, Albert Perlas, Enrique Rayo, Michael Biggel, Stefan Kesselheim, Nicole Borel, Edward J Martin, Constanza B. Venegas, Michael Schloter, Kathrin Schröder, , Lara Urban

This paper introduces a computational framework using nanopore sequencing and deep learning to infer microbial viability from raw signal data, showing high accuracy in controlled and real-world applications.

GigaScience · Jan 1, 2025Peer-reviewedBioinformatics