Modeling cell migratory persistence through temporal correlations and angular noise

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dc.catalogadorjca
dc.contributor.authorMontenegro Rojas, Ignacio
dc.contributor.authorAndaur Lobos, Martín
dc.contributor.authorSoler, Karol
dc.contributor.authorCastelli Lacunza, Diego
dc.contributor.authorBertocchi, Cristina
dc.contributor.authorMatzavinos, Anastasios
dc.contributor.authorRavasio, Andrea
dc.date.accessioned2025-09-22T16:12:45Z
dc.date.available2025-09-22T16:12:45Z
dc.date.issued2025
dc.description.abstractThe persistence of cell migration is a fundamental property of motile behavior, enabling cells to maintain directionality while adapting to fluctuations and external cues. This feature underlies essential processes such as development, immune responses, and cancer invasion. Classical mathematical models have offered key insights into directed migration, yet they often neglect temporal correlations arising from cellular mechanisms that stabilize polarity and protrusion dynamics, processes not well captured by simple white noise. Here, we introduce an agent-based model based on stochastic differential equations (SDEs) that integrates fractional Brownian motion (fBm) to explicitly incorporate translational autocorrelation in cell trajectories. We simulate migration as a function of angular reorientation (D r ) and the strength of correlated noise (H). In this framework, temporal correlation stabilizes trajectory features inherited from initial conditions, whereas angular reorientation introduces variability that enables transitions between erratic and directed motion. Our simulations show that, unlike models driven by white noise, positive correlation markedly enhances persistence even under strong angular reorientation. Moreover, the combination of D r and H gives rise to emergent behaviors, particularly in the presence of taxis, where persistence and responsiveness are jointly tuned. These results identify correlated noise as a proxy for intrinsic cellular memory and provide a versatile computational framework to interpret the diversity and complexity of migratory behaviors.
dc.fechaingreso.objetodigital2025-09-22
dc.format.extent25 páginas
dc.fuente.origenORCID
dc.identifier.urihttps://doi.org/10.1101/2025.08.28.672905
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/105714
dc.information.autorucEscuela de Ingeniería;Montenegro Rojas, Ignacio Tomás;S/I;1045303
dc.information.autorucEscuela de Ingeniería;Andaur Lobos, Martín Didier;S/I;1133054
dc.information.autorucEscuela de Ingeniería;Castelli Lacunza, Diego Ernesto;S/I;1045078
dc.information.autorucFacultad de Ciencias Biológicas;Bertocchi, Cristina;0000-0003-0907-1318;1078032
dc.information.autorucInstituto de Ingeniería Matemática y Computacional;Matzavinos, Anastasios;S/I;1206701
dc.information.autorucInstituto de Ingeniería Biológica y Médica;Ravasio, Andrea;S/I;1071356
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final25
dc.pagina.inicio1
dc.rightsacceso abierto
dc.subjectMechanobiology
dc.subjectCell Migration
dc.subjectFractional Brownian Motion
dc.subjectComputational Biology
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleModeling cell migratory persistence through temporal correlations and angular noise
dc.typeartículo
sipa.codpersvinculados1045303
sipa.codpersvinculados1133054
sipa.codpersvinculados1045078
sipa.codpersvinculados1078032
sipa.codpersvinculados1206701
sipa.codpersvinculados1071356
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