Second SOS Workshop “Self-organization in space and time”
Date: Friday, December 1, 2023
Location: S3|06, 146 and Self-Organizing Systems 2nd floor
The workshop will bring together researchers from computational modeling and experimental biological research. It will shed light on self-organising principles acting on the microscopic and macroscopic scale and on the utilisation of computational techniques such as machine learning for uncovering those principles. Invited talks will feature interdisciplinary research at the cross-road of molecular biology and applied mathematics.
The workshop is open to all researchers and students interested in the intersection between biology and computational analysis. Please send an email to office@bcs.tu-darmstadt.de if you want to participate in the workshop.
| 2:00 pm |
Get Together in room 146 in Hans-Busch-Institut, Merckstrasse 25, room 146 Heinz Köppl: Welcome and Introduction |
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2:15 pm |
Jakob Ruess, Inria Institute Pasteur, Paris, France Title: From single cells to microbial consortia and back: stochastic chemical kinetics coupled to population dynamics Abstract: At the single-cell level, biochemical processes are inherently stochastic. Such processes are typically studied using models based on stochastic chemical kinetics, governed by a chemical master equation (CME). The CME describes the time evolution of the probability distribution over system states and has been a tremendously helpful tool in shedding light on the functioning of cellular processes. However, single cells are not living in isolation but are part of a growing population or community. In such contexts, stochasticity at the single-cell scale leads to population heterogeneity and cells may be subject to population processes, such as selection, that drive the population distribution away from the probability distribution of the single-cell process. Here, I will introduce a multi-scale modeling framework that allows one to capture coupled stochastic single-cell and population process. I will show that the expected population distribution of such multi-scale models can be calculated by solving a modified version of the CME that is of the same dimensionality as the standard CME. I will then show how such models can be used to explain experimental data on plasmid copy number fluctuations and population growth in media that selects against cells that have lost the plasmid. Finally, I will present an optogenetic recombination system that allows one to partition yeast populations into different cell types via external application of blue light to cells and show how our modeling framework can be used to predict and control emerging dynamics of the population composition in response to time-varying light stimuli. |
| 2:55 pm |
Nicole Radde, Mathematical Modeling and Simulation of Cellular Systems, University of Stuttgart, Germany Title: On Moment Closure Approaches for the Chemical Master Equation Abstract: The Chemical Master Equation (CME) is a stochastic approach to describe the evolution of a (bio)chemical reaction system. Its solution is a time-dependent probability distribution on all possible micro-states of the system. As this number is typically large, the CME is often practically unsolvable. The Method of Moments (MoM) reduces the system to the evolution of a few moments, which are described by ordinary differential equations. Those equations are not closed, since lower order moments generally depend on higher order moments. Various closure schemes have been suggested to solve this problem. In my talk I shortly recap the theory behind the CME and the MoM, and discuss selected closure schemes in more detail. Results are shown and discussed on different benchmark systems. |
| 3:35 pm |
Coffee break in the foyer in front of room 250 |
| 4:00 pm |
Stefan Häusler, Computational Neuroscience, LMU München, Germany Title: Correlations reveal the hierarchical organization of networks with latent binary variables Abstract: Deciphering the functional organization of large biological networks is a major chal- lenge for current mathematical methods. A common approach is to decompose net- works into largely independent functional modules, but inferring these modules and their organization from network activity is difficult, given the uncertainties and in- completeness of measurements. Typically, some parts of the overall functional orga- nization, such as intermediate processing steps, are latent. We show that the hidden structure can be uniquely determined from the statistical moments of observable net- work components alone, as long as the mean of each latent variable maps onto a scaled expectation of a binary variable and the functional relevance of the network components lies in their mean values. Whether the function of biological networks permits a hierarchical modularization can be falsified by a correlation-based statistical test that we derive. We apply the approach to gene regulatory networks, dendrites of pyramidal neurons, and networks of spiking neurons. |
| 4:40 pm |
Dmitriy Shutin, Institute for Communication und Navigation, DLR, Oberpfaffenhofen, Germany Title: Swarm Exploration on Earth and beyond Abstract: In contrast to state-of-the-art robotic rovers for Mars or Moon exploration, future robotic platforms will likely consist of multiple units, forming swarms or teams to provide large spatial sensing aperture, increased efficiency, and robustness. In this talk we will discuss methodology as well as recent advances in multi-agent communication, navigation and cooperative exploration. A special focus will be on swarm exploration algorithms – methods for cooperative analysis and decision making in data-limited scenarios. Some applications for planetary space exploration, as well as spin-off applications on Earth will be discussed. |
| 5:20 pm |
Labtour Visit of the SOS lab including lab rooms on first floor in S3|06 |
| 6:00 pm | Closing and get together in the foyer on 2nd floor and within the area of SOS |
