Dr. Christoph Mark

• Job title: Post-Doc
• Working group: Biophysics Group
• Address:
  
  Room 02.076
• Phone number: +49 9131 85-25604
• Email: christoph.mark@fau.de

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Trained physicist, likes probabilistic models and complex systems, from migrating cancer cells, tumors and the immune system to financial markets. Always searching for patterns in biological and financial data.

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Google Scholar – GitHub – LinkedIn – Twitter

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Research projects

Immune cell trafficking and tumor infiltration

The fast migration of immune cells in 3D biopolymer networks such as collagen normally does not allow them to build mature focal adhesions to adhere to the ECM. However, when narrow pores constrict the migration path of the cell, immune cells are able to exert substantial traction forces onto the ECM to overcome steric hindrance. We investigate the regulation of these cell-generated traction forces and how immune cells strive in mechanically challenging environments using 3D traction force microscopy, 3D migration assays, and advanced statistical filtering.

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Collective forces of tumor spheroids

Tumor spheroids are simplified tumor models that are grown in-vitro and usually consist of 1000-20000 individual cancer cells. When embedded in 3D collagen gels, the cells collectively pull on the surrounding matrix, resulting in substantial alignment and stiffening of the collagen fibers. The forces involved in this tissue remodeling process can be calculated by measuring the matrix deformations in the equatorial plane of the embedded spheroid and applying a non-linear material model. This method can easily be applied using normal brightfield microscopy, the protocols of the eLife publication, and the open-source software jointforces.

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Modeling complex systems as heterogeneous stochastic processes

Many complex systems, from migrating cancer cells to financial markets, can be described by random walks. However, these random walks are not homogeneous, as the parameters of the random fluctuations (such as magnitude and autocorrelation) themselves fluctuate over longer time scales. These longterm fluctuations often indicate systematic changes in the behavior of the system, such as changes in cell behavior due to variations in the microenvironment, or changes of the market conditions due to rising inflation. I have developed a novel Bayesian filtering method that allows to extract both abrupt and gradual parameter changes from time series data that contains random fluctuations. The method has been used to understand cell migration in different environments (Nature Communications, 2015) dynamic regulation of forces during cell migration (Nature Methods, 2016), as well as the analysis of financial markets, climate data, and accident data (Nature Communications, 2018).

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