Application Area 1 “Mechanisms of Life”
In recent years, there has been a revolution in the capability to measure and observe the processes of life on many temporal and spatial scales. Simultaneously, our ability to perform extensive simulations of molecular, cellular, and tissue-scale processes has substantially improved and will continue to do so.
Math-centered research in Berlin is internationally leading in the field of data-based simulation of molecular mechanisms of life and their integration into cellular processes.
AA1 is focused on extending this expertise towards spatiotemporal modeling and simulation across the molecular and cellular scales, from pushing time-scale and accuracy barriers via new AI-based quantum dynamics and integration of transfer-operator based techniques with machine learning to spatio-temporal hybrid models coupling molecular with extra- and intra-cellular processes.
Projects in AA1 target seamless integration of new mathematical approaches with incorporation of experimental data, massive simulation, and/or large-scale data analysis, and contribute to finding new strategies in relevant real-world applications like drug design or targeting virus entry.
Previous denomination of AA1 (2019-2022): Life Sciences
Projects marked with an asterisk (*) are short-term one-year pilot projects.
Scientists in Charge: Edda Klipp, Frank Noé, Christof Schütte
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- AA1-6: Data-Driven Modeling from Atoms to Cells
Frank Noé, Cecilia Clementi, Christof Schütte
- AA1-10: New Methods for Inhibiting Sars-Cov2 Cell Entry
Frank Noé, Oliver Daumke
- AA1-14: Development of an Ion-Channel Model-Framework for In-vitro Assisted Interpretation of Current Voltage Relations
Jürgen Fuhrmann, Manuel Landstorfer, Barbara Wagner
- AA1-15: Math-Powered Drug-Design
Konstantin Fackeldey, Christof Schütte, Vikram Sunkara, Christoph Stein, Marcus Weber, Stefanie Winkelmann
- AA1-17: Beyond Attractors: Understanding the Transient and Modular Behaviour of Boolean Networks
Elisa Tonello
- AA1-18: Synchronization and Geometric Structures of Stochastic Biochemical Oscillators
Maximilian Engel, Felix Höfling, Stefanie Winkelmann
- AA1-19: Drug Candidates as Pareto Optima in Chemical Space
Konstantin Fackeldey, Christof Schütte, Vikram Sunkara, Jörg Rademann, Marcus Weber, Stefanie Winkelmann
- AA1-20: Geometric Learning for Single-Cell RNA Velocity Modeling
Daniel Baum, Tim Conrad, Christof Schütte, Vikram Sunkara, Christoph von Tycowicz
Successfully completed projects:
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- AA1-1: The Spatio-Temporal Modelling of Mechanisms Underlying Pain Relief via the µ-Opioid Receptor
Martin Lohse, Christof Schütte, Christoph Stein, Marcus Weber, Stefanie Winkelmann
- AA1-2: Learning Transition Manifolds and Effective Dynamics of Biomolecules
Péter Koltai, Stefan Klus, Klaus-Robert Müller, Christof Schütte
- AA1-3: Stochastic Analysis of Particle Systems: Langevin Dynamics and the Dean-Kawasaki Model
Peter Karl Friz, Ralf Kornhuber, Nicolas Perkowski
- AA1-4: Algebraic Methods for Investigating Cell Fate Decisions
Heike Siebert, Christian Haase
- AA1-5: Space-Time Stochastic Models for Neurotransmission Processes
Christof Schütte, Stephan Sigrist, Stefanie Winkelmann
- AA1-7: Yeast Mating in Space and Time
Edda Klipp
- AA1-8: Random Bifurcations in Chemical Reaction Networks
Maximilian Engel
- AA1-9: Polyhedral Geometry of Virus Capsids
Michael Joswig, Marta Panizzut, Bernd Sturmfels
- AA1-11*: Receptor Dynamics and Interactions in Complex Geometries: An Inverse Problem in Particle-Based Reaction-Diffusion Theory
Paolo Annibale, Martin Lohse, Christof Schütte
- AA1-12*:Mathematical Modelling of Cellular Self-Organization on Stimuli Responsive Extracellular Matrix
Sara Checa, Ansgar Petersen, Barbara Wagner
- AA1-13*: Predicting the Clinical Course of COVID-19 Patients
Marcus Weber, Tim Conrad
- AA1-16: Spatial Dynamics of Cell Signalling Explored with Agent-Based Modeling
Edda Klipp, Rune Linding, Caren Tischendorf