Author

Aaron Gadzekpo

Karlsruhe Institute of TechnologyORCID 0000-0002-7438-5367Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biophysics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Assay:DNA methylation· 1 Approach:graph neural network· 1 Assay:long-read sequencing· 1 Approach:machine learning (classical)· 1 Research Focus:sequence-to-function modeling· 1 Approach:simulation· 1 Organism:zebrafish· 1

Frequent Co-Authors

Lennart HilbertiD· 2 shared Kerstin GöpfrichiD· 1 shared Mai P. TraniD· 1 shared Marcel Sobucki· 1 shared Rakesh ChatterjeeiD· 1 shared Vasily ZaburdaeviD· 1 shared Xenia TschurikowiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

Lennart HilbertORCID

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2 papers

Recent·Most cited

Bayesian optimisation and graph-based rheology enable sequence-dependent modelling of DNA materials

Aaron Gadzekpo, Lennart Hilbert

This paper uses Bayesian optimisation and graph-based rheology to model DNA materials by linking sequence design to material properties.

bioRxiv · May 30, 2026 · PreprintBiophysics

Amphiphiles formed from synthetic DNA-nanomotifs mimic the step-wise dispersal of transcriptional clusters in the cell nucleus

Xenia Tschurikow, Aaron Gadzekpo, Mai P. Tran, Rakesh Chatterjee, Marcel Sobucki, Vasily Zaburdaev, Kerstin Göpfrich, Lennart Hilbert

The paper uses DNA-nanomotifs to mimic transcriptional cluster dispersal in stem cells, showing that amphiphilic effects control droplet size and shape.

Nano Letters · Aug 16, 2023Peer-reviewedSynthetic Biology