MULTIMODE

Methodologies and Tools for the Analysis and Design of Multimodal Stochastic Systems

About

In this project we develop novel methods for the analysis of stochastic chemical reaction networks. We mostly focus on networks that exhibit multimodal behaviour and exhibit a countable finite number of modes. Modes are regions of the state space in which the process spends most of its time. Multimodality plays a central role in probabilistic decisions found in cellular processes. These decisions can explain the phenotypic variability of monoclonal cells. The analysis of such models entails several interesting tasks:

  • The location and relative strength of the modes
  • A model decomposition along the system modes
  • Reconstruction of the mode-conditioned distributions

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Funding

Deutsche Forschungsgesellschaft (DFG)

Publications

  • G. Großmann, J. Zimmerlin, M. Backenköhler, V. Wolf: GINA: Neural Relational Inference From Independent Snapshots. 2021. ( pre-print)

  • M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models. (to appear at QEST 21), 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics. PLOS ONE, 2021. ( pre-print)

  • M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: Analysis of Markov Jump Processes under Terminal Constraints. Tools and Algorithms for the Construction and Analysis of Systems (TACAS), Springer LNCS 12651 pp. 210-229, 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Epidemic Overdispersion Strengthens the Effectiveness of Mobility Restrictions. (HSCC 21), 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, J. Klesen, V. Wolf: Learning Vaccine Allocation from Simulations. 9th International Conference on Complex Networks and their Applications, 2020. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study. 17th International Conference on Quantitative Evaluation of SysTems (QEST), Springer LNCS, 2020. ( pre-print)

  • M. Backenköhler, L. Bortolussi, V. Wolf: Bounding Mean First Passage Times in Population Continuous-Time Markov Chains. 17th International Conference on Quantitative Evaluation of SysTems (QEST), Springer LNCS, 2020. ( pre-print)

  • G. Großmann, M. Backenköhler: Poster Abstract: Birth-Death Processes Reproduce the Infection Footprint of Complex Networks, 7th International Workshop on Hybrid Systems Biology (HSB), Springer LNCS, 2020. ( pre-print)

  • M. Backenköhler, L. Bortolussi, V. Wolf: Control Variates for Stochastic Simulation of Chemical Reaction Networks. 17th International Conference on Computational Methods in Systems Biology (CMSB), Springer LNCS 11773 pp. 42-59, 2019. ( pre-print)

  • P. Kurasov, D. Mugnolo, V. Wolf: Analytic solutions for stochastic hybrid models of gene regulatory networks. Journal of Mathematical Biology 82.1, pp. 1-29, 2021. ( pre-print)

  • P. Kurasov, A. Lück, D. Mugnolo, V. Wolf: Stochastic hybrid models of gene regulatory networks – A PDE approach, Mathematical biosciences 305, pp. 170-177, 2018. ( pre-print)