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Quantitative modeling has become an essential tool in modern biology, driven by advances in both experimental techniques and theoretical frameworks. Powerful high-resolution techniques now provide detailed datasets spanning molecular to tissue scales, allowing visualization of cellular structures with unprecedented detail. In parallel, developments in soft and active matter physics have established a robust theoretical basis for describing biological systems. In this context, two main modeling paradigms have emerged: particle-based models, which explicitly represent discrete components and their interactions, and continuum models, which describe systems through spatially varying fields. We compare these approaches across biological scales, highlighting their respective strengths, limitations, and domains of applicability. To keep our discussion biologically relevant, we focus on five systems of fundamental importance: the cytoskeleton, membranes, chromatin, biomolecular condensates and tissues. With this review, we aim to provide a framework for both theorists and experimentalists to select appropriate modeling strategies, and highlight future directions in biophysical modeling.
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Sorichetti et al. (2026) studied this question.
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