1 citations · 1 across the 3 of their papers we have counts for
6 papers
Inverse statistics of active matter trajectories to distinguish interaction kernel anisotropy from emergent correlations
Simon F. Martina-Perez
High-resolution imaging provides dense trajectories of migrating cells, flocking animals, and synthetic active particles, from which interaction laws can be determined with a wide…
Modelling collective cell migration in a data-rich age: challenges and opportunities for data-driven modelling
Ruth E. Baker, Rebecca M. Crossley, Carles Falco +1
Mathematical modelling has a long history in the context of collective cell migration, with applications throughout development, disease and regenerative medicine. The aim of model…
Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse
Simon F. Martina-Perez, Luke A. Heirene, Jennifer C. Kasemeier +2
Neuroblastoma is a paediatric extracranial solid cancer that arises from the developing sympathetic nervous system and is characterised by an abnormal distribution of cell types in…
Optimal control in combination therapy for heterogeneous cell populations with drug synergies
Simon F. Martina-Perez, Samuel W. S. Johnson, Rebecca M. Crossley +3
Cell heterogeneity plays an important role in patient responses to drug treatments. In many cancers, it is associated with poor treatment outcomes. Many modern drug combination the…
Optimal control of collective electrotaxis in epithelial monolayers
Simon F. Martina-Perez, Isaac B. Breinyn, Daniel J. Cohen +1
Epithelial monolayers are some of the best-studied models for collective cell migration due to their abundance in multicellular systems and their tractability. Experimentally, the…
Bayesian uncertainty quantification for data-driven equation learning
Simon Martina-Perez, Matthew J. Simpson, Ruth E. Baker
Equation learning aims to infer differential equation models from data. While a number of studies have shown that differential equation models can be successfully identified when t…