This image shows Vincent Wagner

Vincent Wagner

Research Assistant
Institute for Stochastics and Applications
Mathematical modeling and simulation of cellular systems

Contact


Germany

Office Hours

Please join my personal meeting room after scheduling an appointment.

 

Subject

Data-driven modelling and simulation of biochemical systems (Systems Biology)

All Publications:
  1. Wagner, V., & Radde, N. (2021). SiCaSMA: An Alternative Stochastic Description via Concatenation of Markov Processes for a Class of Catalytic Systems. Mathematics, 9, 1074. https://doi.org/10.3390/math9101074
  2. Wagner, V., Castellaz, B., Oesting, M., & Radde, N. (2022). Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation. OUP Bioinformatics, 38, 4352–4359. https://doi.org/10.1093/bioinformatics/btac501
  3. Wagner, V., Höpfl, S., Klingel, V., Pop, M. C., & Radde, N. E. (2022). An inverse transformation algorithm to infer parameter distributions from population snapshot data. IFAC-PapersOnLine, 55(23), Article 23. https://doi.org/10.1016/j.ifacol.2023.01.020
  4. Wagner, V., Strässer, R., Allgöwer, F., & Radde, N. E. (2023). A provably convergent control closure scheme for the Method of Moments of the Chemical Master Equation. Journal of Chemical Theory and Computation, 19(24), Article 24. https://doi.org/10.1021/acs.jctc.3c00548
  5. Wagner, V., & Radde, N. (2023). The impossible challenge of estimating non-existent moments of the Chemical Master Equation.
  6. Adam, S., Anteneh, H., Hornisch, M., Wagner, V., Lu, J., Radde, N., Bashtrykov, P., Song, J., & Jeltsch, A. (2020). DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation. Nat. Communications, 11(1), Article 1. https://doi.org/10.1038/s41467-020-17531-8
  7. Höpfl, S., Tautenhahn, H.-M., Wagner, V., & Radde, N. E. (2024). Marginal Percentile Intervals in Bayesian Inference are Overconfident. IFAC-PapersOnLine.
  8. Wagner, V., Jantz, L., Briem, H., Sommer, K., Rarey, M., & Christ, C. (2017). Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation. ChemMedChem, 12, 1866–1872. https://doi.org/10.1002/cmdc.201700478

since 12/2019

Research assistant first at the Institute for Systems Theory and Automatic Control, later at the Institute for Stochastics and Applications of the University of Stuttgart, Germany.

10/2017-11/2019

Master studies Simulation Technology at the University of Stuttgart, Germany

  • Study Focus:
    Numerics
    Modelling
    Scientific Computing
    Computer Vision

Summerterm 2017

Internship: Bayer AG, Berlin

Winterterm 2016/2017

Internship: King Abdullah University of Science and Technology, KSA

10/2013-09/2017

Bachelor studies Simulation Technolgy at the University of Stuttgart, Germany

  • Study Focus:
    Calculus
    Scientific Computing
    Machine Learning

06/2013

Abitur at Schule Schloss Salem, Überlingen, Germany
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