Welcome speech by Béla Merkely, Rector of Semmelweis University and Roland Molontay, the Director of the Organizing Comittee.

Methods for generating spatial omics data are going through a fast technology development, and they are being applied to exploring the tissue microenvironment in health and disease. However, the analysis of this high-dimensional data is challenging. I will discuss strategies for overcoming these challenges including self-supervised learning approaches to learn the structure of the data, and methods for building simple models of the data and evaluating these models using simulations. I will show examples of how these two complementary strategies, one modeling the data using a large number of parameters and the second one using few parameters, can be applied to understanding the tissue microenvironment.

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Due to the availability of data and corresponding computing capacities, more and more cognitive tasks can be assigned to computers that learn independently to improve our understanding, increase our problem-solving capacity or simply help us remember. In this way, artificial intelligence (AI) systems are finding more and more niches in which they can improve our capabilities not only physically but also intellectually. In recent years, we focused on a systematic collection of data to get a deep understanding of biological entities and the relations among them. Starting with the classification and current developments in the field of AI, this talk will give an overview of how the data is collected, curated and employed. Specifically, how such data can be used to develop practical applications for biological sequence analyses, how to combine multiple data modalities to identify disease-causing biomarkers, and how to develop explainable applications for drug repurposing and repositioning.

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Session Chair: under arrangement

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Virtually all processes in health and disease rely on the careful orchestration of a large number of diverse individual components ranging from molecules to cells and entire organs. Networks provide a powerful framework for describing and understanding these complex systems in a holistic fashion. They offer a unique combination of a highly intuitive, qualitative description, and a plethora of analytical, quantitative tools. In my presentation, I will review how molecular networks can be understood as maps for elucidating the relation between molecular-level perturbations and their phenotypic manifestations. I will then sketch out a number of challenges in the areas of network biology and network medicine, as well as recent efforts of my group to address them. These efforts range from methodological work on the visualization and interpretation of large biomedical data combining artificial intelligence with virtual reality technology, to translational efforts towards concrete clinical applications in rare diseases and drug repurposing.

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Venue

The Gala Dinner of the 2nd Biomedical Data Science Conference will be held at the exclusive Urban Betyár. Located in the heart of Budapest at 1051 Budapest, Október 6. utca 16–18, this elegant venue offers a unique blend of Hungarian culinary tradition and modern ambiance. 

How does brain function emerge from the organisation of complex neural systems? What network features enable flexible, adaptive computation across scales? And when these principles are disrupted during development, how do their effects cascade from genes to circuits to behaviour?

This keynote approaches these questions from a systems-level, network-based perspective. Neurodevelopmental disorders provide a powerful test case for this approach: they are intrinsically multiscale, spanning genetic risk, altered developmental trajectories, large-scale network reorganisation, and distributed cognitive and behavioural symptoms. No single level of explanation is sufficient. The central challenge is to trace causal threads across scales and to understand how biological perturbations reshape developing brain networks and their computational capacity.

Drawing on advances in connectomics, genomics, computational modelling, and network science, this talk will explore emerging efforts to bridge these levels of description. By joining the dots from molecules to networks to behaviour, we move closer to a mechanistic account of brain organisation in health and disease - one that may ultimately support more principled biomarkers and therapeutic strategies for neurodevelopmental psychiatric disorders.

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