Author

Vincent Dietrich

University Medical Center of the Johannes Gutenberg University Mainz

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· 2 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:experimental assay· 2 Assay:long-read sequencing· 2 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Susanne GerberiD· 3 shared Anna WierczeikoiD· 2 shared Mark HelmiD· 2 shared Stefan MündnichiD· 2 shared Tamer ButtoiD· 2 shared Alexandra RussoiD· 1 shared Ali Tayefeh YounesiiD· 1 shared Andreas WaltheriD· 1 shared

Activity by Year

2023-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 26 mutual co-author links

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3 shared papersBioinformatics

Susanne GerberORCID

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3 papers

Recent·Most cited

Direct RNA sequencing (RNA004) allows for improved transcriptome assessment and near real-time tracking of methylation for medical applications

Charlotte Hewel, Anna Wierczeiko, Johannes Miedema, Johannes H. Friedrich, Felix Hofmann, Stephan Weißbach, Vincent Dietrich, Laura Holthöfer, Verena Haug, Stefan Mündnich, Lukas Schartel, Lioba Lehmann, Kristi L Jensen, Stefan Diederich, Stanislav Sys, , Susanne Gerber

This study evaluates improvements in direct RNA sequencing (DRS) using RNA004 chemistry and modified-base-calling models, showing enhanced throughput, accuracy, and detection of RNA modifications in clinical applications.

Nucleic Acids Research · Nov 5, 2025Peer-reviewedBioinformatics

Deep Learning Reaction Network: a machine learning framework for modeling time resolved data

Nicolò Alagna, Brigitta Dúzs, Vincent Dietrich, Ali Tayefeh Younesi, Livia Lehmann, Ronald Ulbricht, Heinz Koeppl, Andreas Walther, Susanne Gerber

The paper introduces DLRN, a deep learning framework that models time-resolved data to extract kinetic reaction networks, time constants, and amplitudes with performance comparable to or better than classical methods.

Communications Chemistry · May 15, 2025Peer-reviewedBiophysics

NanopoReaTA: a user-friendly tool for nanopore-seq real-time transcriptional analysis

Anna Wierczeiko, Stefan Pastore, Stefan Mündnich, Anne Busch, Vincent Dietrich, Mark Helm, Tamer Butto, Susanne Gerber

NanopoReaTA provides a user-friendly tool for real-time RNA-seq analysis of nanopore sequencing data, enabling interactive decision-making during sequencing.

Bioinformatics · Aug 1, 2023Peer-reviewedBioinformatics