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Models for Dynamic Cellular and Subcellular Data

Models that represent cells as self-organizing and adaptive are critical for enabling the simulation of multi-cellular systems. These should incorporate subcellular data from experimental techniques tracking individual molecules within cells in real time, as well as capture the fundamental interaction between external and internal molecular environment.

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Cellular state is a multifaceted and complex phenomenon, involving multiple overlapping omics layers that vary in time and space. Capturing and representing this multimodal complexity is essential for predictive modeling of cell behavior and for advancing our understanding of cellular function.