Author

Julian Kopp

TU WienORCID 0000-0003-4975-7103Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1 Microbiology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1 Assay:fluorescence / live-cell microscopy· 1

Frequent Co-Authors

Andrew ZicleriD· 1 shared Astrid Rosa Mach-AigneriD· 1 shared Caroline DanneriD· 1 shared Christian ZimmermanniD· 1 shared Frank DelvigneiD· 1 shared Guido Schlögel· 1 shared Jordy T. ZwerusiD· 1 shared Juan A. MartíneziD· 1 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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Focal author (center)Selected co-authorORCID co-authorUnlinked name

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1 shared paperSystems Biology

Andrew ZiclerORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

TU_MyCo-Vision: A Deep Learning Tool for Detection of Cell Morphologies in Fungal Microscopic Images

Kartik J. Deopujari, Matthias Schmal, Caroline Danner, Zainab Abdul Qayyum, Jordy T. Zwerus, Julian Kopp, Mihail Besleaga, Roghayeh Shirvani, Astrid Rosa Mach-Aigner, Robert Ludwig Mach, Christian Zimmermann

The paper introduces TU_MyCo-Vision, a deep learning tool for detecting 13 fungal morphotypes in bright-field images, showing strong performance on Aureobasidium pullulans and other fungal species.

bioRxiv · Jul 23, 2025 · PreprintMicrobiology

Lowering the switching cost related to the activation of burdensome gene circuits promotes cell population homogeneity and productivity

Lucas Henrion, Vincent Vandenbroucke, Juan A. Martínez, Julian Kopp, Samuel Telek, Andrew Zicler, Frank Delvigne

The paper investigates how reducing the switching cost of burdensome gene circuits in E. coli improves population homogeneity and productivity.

bioRxiv · Oct 14, 2024 · PreprintSystems Biology

Optimizing Bioprocessing Efficiency with OptFed: Dynamic Nonlinear Modeling Improves Product-to-Biomass Yield

Guido Schlögel, Rüdiger Lück, Stefan Kittler, Oliver Spadiut A, Julian Kopp, Jürgen Zanghellini, Mathias Gotsmy

OptFed improves product-to-biomass yield in fed-batch bioprocessing by using dynamic nonlinear modeling to optimize feed rate and reactor temperature.

Computational and Structural Biotechnology Journal · Oct 11, 2024Peer-reviewedBioengineering