ZIH-Colloquium 2024
Table of contents
The ZIH colloquium is a public event and takes place usually the 4th Thursday of each month. Below you will find the current and former dates with all necessary information. You are cordially invited!
24 October 2024, 3:00 p.m., APB-1096/ Online BBB:
Juan Jiménez-Sánchez (Department of Mathematical Sciences, Politecnico di Torino, Italy) - „A stochastic discrete mesoscopic simulator of tumor growth: biomarker discovery and therapy optimization“
Increasingly complex in silico modeling approaches offer a way to simultaneously access cancerous processes at different spatio-temporal scales. High-level models, such as those based on partial differential equations, are computationally affordable and allow large tumor sizes and long temporal windows to be studied, but miss the discrete nature of many key underlying cellular processes. Individual-based approaches provide a much more detailed description of tumors, but have difficulties when trying to handle full-sized real cancers. Thus, there exists a trade-off between the integration of macroscopic and microscopic information, now widely available, and the ability to attain clinically-relevant tumor sizes.
In this talk I will put forward a stochastic mesoscopic simulation framework that incorporates key cellular processes during tumor progression while keeping computational costs to a minimum. This framework captures a physical scale that allows both the incorporation of microscopic information, tracking the spatio-temporal emergence of tumor heterogeneity and the underlying evolutionary dynamics, and the reconstruction of clinically sized tumors at the resolution of standard medical imaging, with the additional benefit of low computational cost.
Then, I will illustrate the application of this modeling framework to two relevant problems in the context of clinical oncology: biomarker discovery, where I will talk about the identification of a novel biomarker for breast and lung cancer, NHOC; and therapy optimization, where I will talk about the search for optimal treatment schedules of temozolomide in glioblastoma, such that patient survival is prolonged, therapy-resistance emergence is delayed, and toxicity is reduced.
Juan Jiménez-Sánchez got his BSc in Biotechnology in 2016 (Universidad Politécnica de Madrid, Spain), and after earning a MSc in Biophysics (Universidad Autónoma de Madrid, Spain), he received his PhD in Physics and Mathematics for his work at the Mathematical Oncology Laboratory (MOLAB), under the supervision of Víctor M. Pérez-García. Currently, he is a postdoctoral fellow at the Politecnico di Torino (Italy), working with Tommaso Lorenzi on the mathematical modeling of muscular dystrophies. His interests lie on the mathematical and computational modeling of tumor growth and evolution, with a strong focus on clinical applications, and more specifically, on therapy optimization using virtual clinical trial approaches.
29 August 2024, 3:00 p.m., APB-1096/ Online BBB:
Shalu Dwivedi and Univ.-Prof. Dr. Stefan Schuster (Dept. of Bioinformatics, Friedrich Schiller University, Jena, Germany) - „Using game theory to elucidate microbial and cancer pathogenesis“
A useful methodology to study emergent properties in biology is Game Theory. It can be applied in the frequent situation where the fitness of a cell or organism does not only depend on its own properties (considered here as strategies) but also on those of other cell or organisms.
In this talk, we will outline the fundamentals of Game Theory as applied in biology. Then we present two applications of game theoretical modeling. In host-pathogen interactions, hosts often produce a toxin and pathogens often produce an enzyme neutralizing the toxin. We conceptualize this as a defense and counter-defense. Our study reveals a paradox: If the inactivating enzyme is very efficient, the toxin becomes useless. If the toxin is no longer produced, the enzyme becomes useless, so that production of the toxin becomes useful again. Does this lead to an oscillatory change in strategies or instead to a steady state? Under certain conditions, we obtain ‘partial (counter-)defense’ strategies as stable equilibria in this game.
Several types of cancer cells are able to “decide” between staying at a primary site or to form metastases. To understand this so-called “go-or-grow” dichotomy better, we again use game theory. We start from a game-theoretical model proposed by Andreas Deutsch’s group. We determine the types of game, depending on parameter values, both for the basic model and for five modified variants that we suggested. We discuss our predictions in terms of the pros and cons of caloric restriction, limitation of the supply of vitamins or methionine.
Shalu Dwivedi got her Master of Science (M.Sc.) degree in Applied Mathematics from Indian Institute of Technology Roorkee (IITR), India and completed a one year research program in Industrial and Applied Mathematics (Fundamental Data Science) at Grenoble Alpes University, France. Since April 2021, she is pursuing her Ph.D. in Stefan Schuster’s lab in the Department of Bioinformatics, Friedrich Schiller University, Jena. She applies game theory and dynamical system modeling to analyze defense and counter-defense in host-pathogen interactions, and also metastasis in tumor cells.
Stefan Schuster earned a Diploma degree in biophysics in 1986 and a PhD degree in 1988, both at Humboldt University in Berlin under the supervision of Reinhart Heinrich. After being a postdoc in Berlin, Bordeaux and Amsterdam, he became a lecturer at Humboldt University in 1993 and a full professor in bioinformatics at the University of Jena in 2003. His main research interests are the modelling of metabolic networks, evolutionary game theory, biological oscillations and host-pathogen interactions.
22 August 2024, 3:00 p.m., WIL-A317/ Online BBB:
Johannes Langguth (University of Bergen, Norway) - „Graph Algorithms on Emerging Tile-Centric Accelerators“ slides
A major recent development in computer hardware was the rise of dedicated accelerator hardware for machine learning applications such as the Graphcore IPUs and Cerebras WSE. These processors have evolved from the experimental state into market-ready products, and they have the potential to constitute the next major architectural shift after GPUs saw widespread adoption a decade ago.
A salient feature of these devices is the use of SRAM for memory, which offers very low latency and high bandwidth, making them attractive for a wide range of graph algorithms. On the other hand, the wide parallelism employed in these devices makes it difficult to use them efficiently for irregular computations.
In this talk we will present the new hardware and discuss the programming techniques that are required to unlock their potential. We present implementations of basic graph algorithms and show early results on the attainable performance, as well as comparisons to other architectures. We follow up by discussing the wider implications of the architecture for algorithm design and programming.
Johannes Langguth is a Senior Research Scientist at Simula Research Laboratory, and an Associate Professor at the University of Bergen, Norway. Prior to that, he worked at ENS Lyon, France. His research is centred around architectures, algorithms, and applications of parallel graph algorithms and sparse linear algebra. His previous projects include interdisciplinary work on social network analysis using combinations of network science, GNNs, and NLP, as well as parallel matching algorithms for combinatorial scientific computing and performance optimization for irregular applications the European High-Performance Computing project SparCity. Recent work has focussed on graph algorithms on tile-centric accelerators such as Graphcore IPUs and Cerebras WSEs, providing the first implementations of several algorithms on these platforms.
27. June 2024, 3:00 p.m., WIL-A317/ Online BBB:
Dr. Joachim Jenke (RWTH Aachen University, Germany) - „Tool support for HPC performance optimization and productivity services“ slides
In the context of POP CoE and NHR4CES we provide services to HPC code developers. With the help of different performance analysis tools we provide performance assessments. With the help of correctness analysis tools we assert the correct use of MPI and OpenMP in these codes. This talk will focus on recent developments of the tools Archer and MUST for correctness analysis as well as OTF-CPT as a lightweight tool prototype to perform scalability measurements and identify performance model factors.
Joachim Jenke, né Protze, got his Diploma in computer science from TU Dresden in 2011 and his PhD in computer science from the RWTH Aachen University in 2021. Currently, he is working as research staff in the High Performance Computing group at the IT Center at RWTH. His research interests have a focus on debugging and correctness of parallel programs, especially detecting data races and deadlocks. He leads the development of the production-level HPC debugging tools MUST and ARCHER. Joachim is leading the development of tool extensions for the OpenMP and MPI standards.
30 April 2024, 3:00 p.m., APB-1096/ Online BBB:
Dr. Artur César Fassoni (Universidade Federal de Itajubá/ UNIFEI, Brazil) - „Mathematical insights for immuno-oncology: side effects in CAR-T cell therapy, and plasticity-mediated tumor survival“ slides
In this talk, I'll discuss ongoing research on two topics in mathematical oncology. In the first part, I'll present an ordinary differential equation model for cytokine release syndrome (CRS) in chimeric antigen receptor (CAR) T-cell therapy. While CAR T-cell therapy is promising, CRS is a common clinical challenge. We developed a model for CRS that was calibrated with data from 25 patients with different responses. Using time-scale arguments, we relate the shape of the response curves to interpretable model parameters. Considering three known mechanisms of macrophage activation, we identify the CD40-CD40L axis as the primary driver of CRS, providing a clinically viable target to overcome CRS. In the second part, I'll present a partial differential equation model of tumor progression and survival mediated by phenotypic plasticity. Motivated by the role of population heterogeneity in cancer progression and treatment, we develop an integro-differential model that describes tumor heterogeneity within an aspect space of cell phenotypes. By introducing diffusion in the aspect space, we define a tumor plasticity parameter as the diffusion coefficient. Numerical simulations illustrate different scenarios with tumor survival and extinction dynamics.
Artur C. Fassoni studied Mathematics at the Federal University of Viçosa, in Brazil, and received his Ph.D. in Applied Mathematics from the State University of Campinas in 2016 for his work on mathematical oncology. Since 2013, he has been a professor of mathematics at the Federal University of Itajubá in Brazil. In 2017, he was a visiting scientist at the Institute of Medical Informatics and Biometry (IMB) at TU Dresden. His research deals with mathematical models in the field of immuno-oncology, focusing on leukemias and CAR T-cell therapy, approaching both applied and theoretical aspects. He received an Alexander von Humboldt fellowship for experienced researchers for a second stay at the IMB/TUDresden, working with Prof. Dr. Ingmar Glauche.
14 March 2024, 3:00 p.m., WIL-A317/ Online BBB:
Prof. Athanasius F. M. (Stan) Marée (School of Biosciences, Cardiff University, UK) - „A multi-level biophysical approach to cell motility to unravel gastrulation and somitogenesis“
The first segmented structures to appear in developing vertebrate embryos are the somites, defining the principal axis and segmentation of the animal's body plan. Somitogenesis follows a clock-like rhythm, and a range of molecular "gears" of this "clock" have been identified with expressions oscillating at that same frequency. In my talk I will argue that to unravel the mechanisms underlying this intricate morphogenetic process it is key to link our understanding of the gene regulatory processes and cell-cell signalling to the biophysics of deformation, adhesion, motility and directed migration of the cells involved. After convincing ourselves that the Cellular Potts Model is indeed a powerful framework to correctly capture such biophysical processes, I will focus on chick somitogenesis and, using the Cellular Potts Model as an integrative unit, show that the known biomolecular network and modifications in chemotaxis and adhesion can not only explain the formation of the principle axis during gastrulation, but also the segmentation into somites as a consequence of a self-organised transition from a temporal to a spatial pattern. Through this study we identify which aspects of the mechanism are robust and which are more sensitive for the specific molecular and biophysical circumstances. We will discuss how this can be related to evolutionary conserved mechanisms, and predict at which steps of the developmental process divergent solutions between species should be expected.
Stan Marée had studied biology at Utrecht University, The Netherlands, and received his PhD in Theoretical Biology and Bioinformatics in 2000 from Utrecht University for his work on mophogenesis of Dictyostelium discoideum. After a PostDoc in Mathematical Biology at the University of British Columbia, Canada, and as a staff member in the Theoretical Biology and Bioinformatics Group at Utrecht University, he founded his research group in 2010 at the Department of Computational and Systems Biology, John Innes Centre in Norwich, UK. Since 2019, Stan Marée holds the Chair in Systems and Predictive Biology at the School of Biosciences, Cardiff University, UK. He has developed, together with Paulien Hogeweg, Leah Edelstein-Keshet and Veronica Grieneisen, some of the most insightful and comprehensive computational models of self-organised patterning, of tissue morphogenesis, of cell polarity and cell motility from social microorganisms to animals to plant tissues.
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