BIOMAT 2023: Schedule
 | MONDAY June 12th | TUESDAY June 13th | WEDNESDAY June 14th | THURSDAY June 15th | FRIDAY June 16th |
9:30 10:20 | Mathematical modelling of self-organisation during embryonic development - Dagmar Iber ETH Zurich | Topological Data Analysis for Oncology - Bernadette Stolz-Pretzer École Polytechnique Fédérale de Lausanne | Bridging between higher-order mechanisms and higher-order phenomena - Giovanni Petri CENTAI Institute | Collective cell motility - Jean-François Joanny Collège de France | |
10:20 10:50 | Contributed Talk Model selection for time-reversible evolutionary models via linear invariants - Roser Homs Centre de Recerca Matemàtica | Contributed Talk Phylogenetic reconstruction for time reversible models - Angelica Torres Centre de Recerca Matemàtica | Contributed Talk Optimal growth patterns in embryo development and organism locomotion - Jose Muñoz Universitat Politècnica de Catalunya | Contributed Talk Active Self-Organization of Nematic Architectures on a Curved Deformable Biological Surface - Waleed Mirza Universitat Politècnica de Catalunya | |
10:50 11:20 | COFFEE BREAK + Group Photo | COFFEE BREAK | |||
11:20 12:10 | Mathematical modelling of self-organisation during embryonic development - Dagmar Iber ETH Zurich | Pattern formation in cellular adhesions and the actin cytoskeleton - Marino Arroyo Universitat Politécnica de Catalunya | Epithelial mechanobiology from the bottom up - Xavier Trepat Institute for Bioengineering of Catalonia | TBP - Alfonso Valencia Barcelona Supercomputing Center | |
12:10 13:00 | Bridging between higher-order mechanisms and higher-order phenomena - Giovanni Petri CENTAI Institute | Pattern formation in cellular adhesions and the actin cytoskeleton - Marino Arroyo Universitat Politécnica de Catalunya | Epithelial mechanobiology from the bottom up - Xavier Trepat Institute for Bioengineering of Catalonia | TBP - Alfonso Valencia Barcelona Supercomputing Center | |
13:00 15:00 | REGISTRATION 14:30-14:50 _______ WELCOME 14:50-15:00 | LUNCH | |||
15:00 15:50 | Collective cell motility - Jean-François Joanny Collège de France | Collective cell motility - Jean-François Joanny Collège de France | Bridging between higher-order mechanisms and higher-order phenomena - Giovanni Petri CENTAI Institute | Topological Data Analysis for Oncology - Bernadette Stolz-Pretzer École Polytechnique Fédérale de Lausanne | Collective cell motility - Jean-François Joanny Collège de France |
15:50 16:20 | Contributed Talk Modeling low-intensity ultrasound mechanotherapy impact in tumor dynamics - Beatriz Blanco Besteiro Universidad de Granada | Contributed Talk Mathematical modelling of vasculature regression during cartilage condensation - Giovanni Dalmasso Centre de Recerca Matemàtica | Contributed Talk Modeling of mixtures of two antibodies with their advantages and disadvantages in infectious diseases: the case of secondary dengue infections - Charlotte Dugourd Claude Bernard University Lyon 1 | Contributed Talk Theoretical and computational framework for upscaling active gels models of the actin cortex to epithelial mechanics, rheology and 3D shaping - Adam Ouzeri Universitat Politècnica de Catalunya | Topological Data Analysis for Oncology - Bernadette Stolz-Pretzer École Polytechnique Fédérale de Lausanne |
16:20 17:00 | COFFEE BREAK | COFFEE BREAK | |||
17:00 17:50 | Mathematical modelling of self-organisation during embryonic development - Dagmar Iber ETH Zurich | Bridging between higher-order mechanisms and higher-order phenomena - Giovanni Petri CENTAI Institute | Emergent synchronization in pairwise and high-order networks: the role of the spectral dimension - Ana Paula Millán Universidad de Granada | ||
17:50 18:40 | Mathematical modelling of self-organisation during embryonic development - Dagmar Iber ETH Zurich | Topological Data Analysis for Oncology - Bernadette Stolz-Pretzer École Polytechnique Fédérale de Lausanne | Emergent synchronization in pairwise and high-order networks: the role of the spectral dimension - Ana Paula Millán Universidad de Granada | ||
20:30 | Social Dinner | ||||
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Mathematical modelling of self-organisation during embryonic development
Dagmar Iber
ETH Zurich
Reproduction of complex life hinges on the reliable translation of the linear information that is contained in our DNA into complex 3D shapes and functions. In this course, I will present chemical and biophysical principles that enable this reliable self-organisation. While there is only a limited number of candidate mechanisms and at times it may be difficult to uncover any candidate mechanism, often more than one mechanism can, in principle, explain the same biological phenomenon. Careful data-based mathematical modelling is therefore important to distinguish between candidate mechanisms. In the last part, I will discuss approaches for data-based modelling and model selection.
Bridging between higher-order mechanisms and higherorder phenomena
Giovanni Petri
CENTAI Institute
In this mini-course we will link together two sides of the recent progresses in higher-order systems.
On the one hand, we will describe recent advances in dynamical systems with interactions among groups of nodes (higher-order interactions) and the novel phenomenologies that stem from them.
On the other one, we will see how recent tools from algebraic topology and multivariate information theory characterise these behaviours in real-world data.
Finally, we will describe the current attempts to infer or reconstruct the original underlying higher-order models from data.
Topological Data Analysis for Oncology
Bernadette Stolz-Pretzer
École Polytechnique Fédérale de Lausanne
Topological data analysis (TDA) is an emerging mathematical field that uses topological and geometric approaches to quantify the “shape” of data. Persistent Homology (PH), the most prominent method from TDA, captures topological invariants such as connected components, loops, and voids in data at multiple scales. The output from PH can be visualised in a barcode which can further be vectorised to enable integration with statistical and machine learning tools. In recent years, PH has been successfully applied to study many biological phenomena.
In this mini course I will introduce the mathematical concepts behind TDA and PH and show applications to both experimental data from oncology and the output from mathematical models. I will in particular demonstrate how PH allows us to quantify the effect of drugs on experimental data of vascular networks of tumours and how we can use similar approaches to stratify the parameter space of a mathematical model of tumour vasculature. I will then show how we can combine TDA and mathematical models to understand the effect of structural features of vascular networks on perfusion level and response to radiotherapy. Finally, I will present how PH can give insight into spatial relations in data and how it can complement machine learning approaches for biological data.