Sonja Mathias

About Myself

I am currently a PhD student within the Division of Scientific Computing at the Department of Information Technology at Uppsala University. As such, I am a member of the Computational Systems Biology group and the HellanderLab on Computational Science and Engineering.

I have a strong background in Mathematics from my MSc studies at the University of Bonn, as well as well-founded skills in Computer Science, Biology and Chemistry through my interdisciplinary BSc studies in Computational Life Science at the University of Lübeck, Germany.

My PhD project under supervision of Andreas Hellander is situated at the interface of Scientific Computing and Computational Systems Biology. The aim is to develop numerical methods to efficiently simulate multicellular systems. We focus on populations of biological cells, such as tissues or bacterial colonies, in which the global behavior over time emerges as a result of the combination of the individual cellular dynamics and cell-cell interactions.

In this context I am involved in a collaboration with the Adameyko Lab for developmental biology at Karolinska institutet studying how cell level processes such as directed cell division can influence cartilage formation during embryonic development.

Publications

Mathias, S., Coulier, A. & Hellander, A. (2022). CBMOS: a GPU-enabled Python framework for the numerical study of center-based models. BMC Bioinformatics 23, 55.
Mathias, S., Coulier, A., Bouchnita, A. & Hellander, A. (2020). Impact of force function formulations on the numerical simulation of centre-based models. Bull Math Biol 82, 132.
Barker, J., Bulin, J., Hamaekers, J., & Mathias, S. (2017). LC-GAP: Localized Coulomb Descriptors for the Gaussian Approximation Potential. In: Griebel M., Schüller A., Schweitzer M. (eds) Scientific Computing and Algorithms in Industrial Simulations. Springer, Cham.
Erb, W., & Mathias, S. (2015). An alternative to Slepian functions on the unit sphere – A space-frequency analysis based on localized spherical polynomials. Applied and Computational Harmonic Analysis, 38(2), 222-241.