Author

Johannes Seiffarth

Forschungszentrum JülichORCID 0000-0002-2087-9847Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Assay:imaging· 3 Research Focus:software / tool· 3 Organism:bacteria (other)· 2 Research Focus:benchmarking· 2 Approach:experimental assay· 2 Research Focus:cell-cell communication· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

Dietrich KohlheyeriD· 3 shared Katharina NöhiD· 3 shared Bastian WollenhauptiD· 2 shared Hanno ScharriD· 2 shared Oliver NeumanniD· 2 shared Ralf MikutiD· 2 shared Tim ScherriD· 2 shared A. KrügeriD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersBioinformatics

Dietrich KohlheyerORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

DNA-intercalating antiphage molecules trigger abortive infection through mutual destruction and synergize with bacterial immunity

Larissa N. Ernst, Cornelia Gätgens, Bente Rackow, Nadiia Pozhydaieva, Elyes Gaaloul, A. Krüger, Johannes Seiffarth, Michelle Bund, Vivien Joisten-Rosenthal, Dietrich Kohlheyer, Björn Usadel, Alexander Harms, Katharina Höfer, Julia Frunzke

Proceedings of the National Academy of Sciences · Jun 3, 2026Peer-reviewedMicrobiology

ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud

Johannes Seiffarth, Tim Scherr, Bastian Wollenhaupt, Oliver Neumann, Hanno Scharr, Dietrich Kohlheyer, Ralf Mikut, Katharina Nöh

ObiWan-Microbi provides a cloud-based platform for semi-automated image annotation in microfluidic live-cell imaging using deep learning segmentation.

SoftwareX · Feb 1, 2024Peer-reviewedBioinformatics

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation

Tim Scherr, Johannes Seiffarth, Bastian Wollenhaupt, Oliver Neumann, Marcel P. Schilling, Dietrich Kohlheyer, Hanno Scharr, Katharina Nöh, Ralf Mikut

microbeSEG provides a deep learning tool for automated cell segmentation in microbial cultures, achieving accurate results within 45 minutes of user time.

PLoS ONE · Nov 29, 2022Peer-reviewedBioinformatics

CellSium - Versatile Cell Simulator for Microcolony Ground Truth Generation

Christian Carsten Sachs, Karina Ruzaeva, Johannes Seiffarth, Wolfgang Wiechert, Benjamin Berkels, Katharina Nöh

CellSium generates synthetic microcolony images for training deep learning segmentation models in microfluidic live-cell imaging.

Bioinformatics Advances · Jan 1, 2022Peer-reviewedBioinformatics