I am a biochemist and bioinformatician working at the intersection of methodological development and applied bioinformatics, with a focus on high-dimensional biological datasets. My work has spanned (meta-)genomics and transcriptomics data from both modern and ancient sources.
 

My current postdoctoral research centers on ancient DNA recovered from cave sediments (sedaDNA). Cave sediments are particularly valuable archives: they preserve precise archaeological context that allows direct links to past human occupation and behavior across timescales exceeding one million years, offering a rare window into the long-term dynamics of cave ecosystems and the communities that inhabited them.
 

During my PhD, I developed computational methods and visualizations to tackle a fundamental challenge in data analysis: uncertainty. Specifically, I investigated how missing values propagate through dimensionality reduction pipelines—such as PCA—and how this affects the reliability and interpretability of low-dimensional representations of complex biological data

2026-present Postdoctoral researcher at the Archaeo- and Paleogenetics group, University of Tübingen, and the Max Planck Institute for Biology (Molecular biology), Tübingen, funded by GACT

2025 Dr. rer. nat. University of Tübingen (Prof. Kay Nieselt, Prof. Philipp Hennig)
Thesis title: Computational Methods for Interpretable Analysis of Uncertain and Incomplete High-Dimensional Biological Data

2022-2025 Research Assistant University of Tübingen, funded by TüKITZMed

2018-2022 Research Assistant University of Tübingen, funded by the Cluster of Excellence – Machine Learning for Science

2015-2018 Bioinformatics M.Sc. University of Tübingen

2011-2014 Biochemistry B.Sc. University of Tübingen

• Zabel, S., Breitling, S., Posth, C., & Nieselt, K. (2025). A probabilistic approach to visualize the effect of missing data on PCA in ancient human genomics. BMC genomics, 26(1), 537.

• Zabel, S., Hennig, P., & Nieselt, K. (2023). VIPurPCA: Visualizing and propagating uncertainty in principal component analysis. IEEE Transactions on Visualization and Computer Graphics, 30(4), 2011-2022.

• Fuhl, W., Zabel, S., & Nieselt, K. (2023). Improving taxonomic classification with feature space balancing. Bioinformatics Advances, 3(1), vbad092.

• Luqman, A., Muttaqin, M. Z., Yulaipi, S., Ebner, P., Matsuo, M., Zabel, S., ... & Götz, F. (2020). Trace amines produced by skin bacteria accelerate wound healing in mice. Communications Biology, 3(1), 277.

• Fan, S. H., Ebner, P., Reichert, S., Hertlein, T., Zabel, S., Lankapalli, A. K., ... & Götz, F. (2019). MpsAB is important for Staphylococcus aureus virulence and growth at atmospheric CO2 levels. Nature communications, 10(1), 3627.

• Natarajan, J., Moitra, A., Zabel, S., Singh, N., Wagner, S., & Rapaport, D. (2019). Yeast can express and assemble bacterial secretins in the mitochondrial outer membrane. Microbial Cell, 7(1), 15.

• Vitali, D. G., Sinzel, M., Bulthuis, E. P., Kolb, A., Zabel, S., Mehlhorn, D. G., ... & Rapaport, D. (2018). The GET pathway can increase the risk of mitochondrial outer membrane proteins to be mistargeted to the ER. Journal of cell science, 131(10), jcs211110.