«Mechanisms of cancer growth, invasion, and progression: a biomathematical modeling analysis»
«Mechanisms of cancer growth, invasion, and progression: a biomathematical modeling analysis»
The event passed
21 Nov 2019
Moscow, 3, Ordzhonikidze st., room 338
About the event

Andreas Deutsch, Professor of Technical University of Dresden, will hold a workshop "Mechanisms of cancer growth, invasion, and progression: a biomathematical modeling analysis".

Professor A. Deutsch (h-index 24) will visit RUDN University   November, 18-25, 2019. He is the head of the department for Innovative Methods of Computing, Centre for Information Services and High Performance Computing (Technical University of Dresden, QS-150-200).

Research of the department is directed at the development of innovative mathematical models and simulation tools to detect organizational principles of selected biological systems. Researchers focus on "cellular systems" which possess a multitude of interaction mechanisms whose cooperative interplay guarantees in particular the development of organismic forms. Disorders in cell interaction can lead to diseases and malignant pattern formation (e.g. tumor growth). Important insights into function and regulation of biological systems can be gained by linking mathematical modeling and computational tools with biological/medical in vitro, and in vivo data. The staff work on interdisciplinary projects on the basis of local, national, and international cooperation. They develop the software Morpheus, a modeling and simulation environment for the study of multiscale and multicellular systems.

There will be a workshop for students of the S.M. Nikolskii Mathematical Institute November, 21 at 15:00.  Applications of finite-difference equations, deterministic and stochastic cellular automata, and lattice-gas cellular automata will be considered. Prof. Deutsch will discuss an integrative modelling approach based on mesoscopic biological lattice-gas cellular automata (BIO-LGCA) to analyze collective effects in cancer invasion. This approach is rule- and cell-based, computationally efficient, and integrates statistical and biophysical models for different levels of biological knowledge. Moreover, prof. Deutsch and his colleagues   have derived BIO-LGCA rules for elementary cell migration and interaction types, and have shown how to construct biophysical BIO-LGCA rules from microscopic biophysical Langevin models for selected cases of single and collective cell migration. In particular, BIO-LGCA have been used for analyzing collective cancer behavior, as the emergence of invasive fronts and an Allee effect based on a growth-migration dichotomy.

The BIO-LGCA modelling strategy is “modular'': starting from “basic models'', coupling of them is required to design models for specific biological or medical problems. The focus of future activities is the analysis of further model combinations for selected biological problems, which are not necessarily restricted to cells but could also comprise interactions at the subcellular and the tissue scale. The resulting multi-scale models will contain a multitude of coupled spatial and temporal scales and will impose challenges for analytic treatment.


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