Jan Hasenauer
  • Life and Medical Sciences Institute (LIMES)
Research topics
  • Systems Medicine
  • Systems Biology
  • Mathematical Modelling
  • Machine Learning
Jan Hasenauer (*1983) studied technical cybernetics at the University of Stuttgart and the University of Wisconsin, Madison. After his studies, he received his PhD in Systems Biology in February 2013. A few months later, he became team leader at the Institute of Computational Biology at Helmholtz Zentrum München. In 2015, he was awarded an independent junior research group at Helmholtz Zentrum München. Since October 2018, he is professor for Mathematics & Life Sciences at the University of Bonn. The research of Jan Hasenauer focuses on the development of methods for data-driven modelling of biological processes. These methods enable model-based integration of different data sets, critical evaluation of available information, comparison of different biological hypotheses and tailor-made selection of future experiments.
Selected publications

Stapor P, Schmiester L, Wierling C, Merkt S, Pathirana D, Lange BMH, Weindl D, Hasenauer J (2022) Mini-batch optimization enables training of ODE models on large-scale datasets. Nat Comm 13:34.

Fröhlich F, Kessler T, Weindl D, Shadrin A, Schmiester L, Hache H, Muradyan A, Schütte M, Lim J-H, Heinig M, Theis FJ, Lehrach H, Wierling C, Lange B, Hasenauer J (2018) Efficient parameter estimation enables the prediction of drug response using a mechanistic pan-cancer pathway model. Cell Syst 7:567-579.e6.

Loos C, Moeller K, Fröhlich F, Hucho T, Hasenauer J (2018) A hierarchical, data-driven approach to modeling single-cell populations predicts latent causes of cell-to-cell variability. Cell Syst 6593-603.e13.

Jagiella N, Rickert D, Theis FJ, Hasenauer J (2017) Parallelization and high-performance computing enables automated statistical inference of multiscale models. Cell Syst 4:194-206.

Jan Hasenauer

Endenicher Allee 64

53115 Bonn

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