6.3. Integration of computational models in understanding protrusion dynamics
Agent-based models (ABMs) simulate the behavior of individual agents (cells) within a defined environment [76]. Integrating ABMs allows researchers to simulate and analyze the emergent properties of lamellipodia and filopodia in response to various stimuli. These models provide a platform for exploring how individual cells contribute to collective invasive behavior and how perturbations at the cellular level propagate through the system. Developing mechanistic computational models that incorporate biochemical and biomechanical processes involved in protrusion dynamics enables a more detailed understanding of the underlying regulatory networks. Computational simulations can predict the effects of genetic or pharmacological interventions on lamellipodia and filopodia dynamics, guiding experimental design and hypothesis generation. Leveraging machine learning and data-driven approaches can uncover hidden patterns within large datasets generated from imaging experiments. Integrating computational algorithms with experimental data facilitates the identification of novel correlations and predictive models, enhancing our understanding of the factors influencing protrusion dynamics [77].