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Prof. Dagmar Iber (ETH Zürich)02/03/2026, 17:20
Computational simulations have long been used to study emergent phenomena in biology. Data-driven in silico models of tissue behavior in development and disease now enable the creation of Digital Twins—virtual counterparts with applications in bioengineering and precision medicine. In this talk, I will present our simulation frameworks for high-resolution tissue modeling and parameter...
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Dr Max Bonomi (Institut Pasteur)02/03/2026, 18:05
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Prof. Stefan Knapp (Goethe University)03/03/2026, 09:00
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Dr Barak Raveh (The Hebrew University of Jerusalem)03/03/2026, 09:45
T cells respond swiftly, specifically, sensitively, and robustly to cognate antigens presented on the surface of antigen presenting cells. Existing microscopic models capture various aspects of early T-cell antigen receptor (TCR) signaling at the molecular level. However, none of these models account for the totality of the data, impeding our understanding of early T-cell activation. Here, we...
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Stephan Preibisch (HHMI Janelia)03/03/2026, 11:45
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Dr Andrej Sali (UCSF)03/03/2026, 14:00
Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ~52 MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving...
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Dr Florian Wilfing (Max Planck Institute of Biophysics)03/03/2026, 14:45
Biomolecular condensates organise cellular biochemistry, yet their molecular architecture in situ remains poorly understood. During selective autophagy, macromolecules frequently accumulate into biomolecular condensates, forming discrete entities for autophagic engulfment and degradation – ideal systems for structural analysis. We employed in situ cryo-electron tomography to determine the...
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Prof. Martin Beck (Max Planck Institute of Biophysics)03/03/2026, 16:45
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Prof. Samantha Wood (Indiana University Bloomington)04/03/2026, 09:00
The origins of perception and cognition have been debated for centuries, with ongoing disagreement about what knowledge and neural structure are hardwired at birth. A major obstacle to resolving this debate is that, until recently, it has been impossible to train formal computational models of intelligence on the same sensory experiences as developing animals. We address this limitation by...
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Prof. Sasha van Albada (FZ Jülich)04/03/2026, 11:00
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Prof. Liesbet Geris (University of Liège, KU Leuven, VPH society)04/03/2026, 14:00
In silico and in vitro technologies are complementary to traditional biological and biomedical tools, enabling the study of multifactorial processes under controlled conditions. In the first part of this talk, I will present examples from bone and joint degeneration and regeneration research, where we combine computer modeling and simulation with microphysiological systems to better understand...
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Dr Loic Royer (Biohub)04/03/2026, 16:45
Imagine having an interactive digital twin of a developing embryo — one you could pause, rewind, or zoom into, exploring how every cell divides, moves, and differentiates. To make this vision real, we created Zebrahub, a dynamic atlas of zebrafish embryogenesis that combines cutting-edge microscopy, powerful computational lineage tracking (Ultrack), and precise molecular mapping into an...
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Dr Annalisa Marsico (Computational Health Center, Helmholtz Munich)05/03/2026, 09:00
Computational analysis of high-resolution CLIP-seq data has enabled precise mapping of RBP binding sites and cis-regulatory elements underlying post-transcriptional RNA regulation. Recently, the field has shifted with the emergence of RNA foundation models—self-supervised models trained on vast unlabeled RNA sequences—that enable holistic modeling of RNA function and in silico hypothesis...
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Dr Judith Zaugg (University of Basel)05/03/2026, 09:45
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Prof. Marcel Schulz (Goethe University and Uniklinikum Frankfurt)05/03/2026, 11:45
Modern applications of AI technologies have enabled to predict the expression of genes genome-wide in a cell-type specific way using DNA sequence or epigenetic information. In this talk I will explain how these methods can be used to build digital twins for modelling gene expression and introduce novel applications for associating genes with disease and suggest personalised drug treatments.
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Prof. Suliana Manley (EPFL - Laboratory of Experimental Biophysics Lausanne)05/03/2026, 14:45
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Prof. Jeffery Hoch (UConn Health)05/03/2026, 16:45
Machine learning is impacting not just the natural sciences but also the social sciences, engineering, architecture, and the art world. In many fields an obstacle to the application of machine learning is the relative paucity of available training data. Other challenges
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include the problem of interpreting the results of a machine learning algorithms, incorporating machine learning into... -
Mr Jan Kosinski (EMBL)05/03/2026, 17:30
One of the central goals of computational biology is to build a realistic model of a cell – one that can simulate cellular processes, predict the effects of perturbations, and support rational drug design. This vision has gained new momentum through recent technological advances, for example, in single-cell omics, structural proteomics, and visual mapping of cells using in-cell cryo-electron...
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