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].