Position Papers of the 20th Conference on Computer Science and Intelligence Systems

DOI: http://dx.doi.org/10.15439/2025F4886

Citation: Position Papers of the 20th Conference on Computer Science and Intelligence Systems, M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 44, pages 99–106 (2025)

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Abstract. Cell aggregation, where cells stick together, is a key process in many biological events like how embryos form, how tissues heal, and how microbes create communities. Studying this involves looking at different types of data, from detailed molecular information to images and patient data. With new technologies, we have access to large amounts of this data in public databases. Analyzing and combining this complex information requires advanced computer methods. While there are challenges in handling and integrating these diverse datasets, exploring them helps us understand basic biology, develop models for diseases, find new drugs, and advance regenerative medicine. This report reviews these data types, sources, and analysis methods to guide research in this important field. Index Terms---Reinforcement Learning, MARL, Cell Mechanics, Cell aggregation

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