Author
A. Tschanz
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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2021-2023 · peak 4/yrCo-Author Collaboration Network
10 top collaborators · 24 mutual co-author links5 papers
Recent·Most cited
Superresolution microscopy reveals partial preassembly and subsequent bending of the clathrin coat during endocytosis
M. Mund, A. Tschanz, Y.-L. Wu, F. Frey, J. L. Mehl, M. Kaksonen, O. Avinoam, U. S. Schwarz, J. Ries
The paper uses superresolution microscopy to show clathrin coats partially assemble on flat membranes before bending, and introduces a model to explain this process.
bioRxiv · Oct 12, 2021Cell Biology
Maximum-likelihood model fitting for quantitative analysis of SMLM data
Y.-L. Wu, P. Hoess, A. Tschanz, U. Matti, M. Mund, J. Ries
LocMoFit is an open-source framework that fits models to SMLM data using maximum likelihood estimation to extract biological insights from single-molecule localization coordinates.
bioRxiv · Aug 30, 2021Biophysics
Systematic Tuning of Rhodamine Spirocyclization for Super-Resolution Microscopy
N. Lardon, L. Wang, A. Tschanz, P. Hoess, M. Tran, E. D'Este, J. Ries, K. Johnsson
This paper describes a method to systematically tune the spirocyclization equilibrium of rhodamines to create probes for different super-resolution microscopy techniques.
bioRxiv · May 20, 2021Cell Biology
Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy
R. Diekmann, J. Deschamps, Y. Li, A. Tschanz, M. Kahnwald, U. Matti, J. Ries
This paper develops an automated pipeline for sCMOS camera characterization using thermal signals, enabling artifact reduction in high- and super-resolution microscopy without additional hardware or user intervention.
bioRxiv · Apr 16, 2021Biophysics