Dynamic modelling of cell cycle arrest through integrated single-cell and mathematical modelling approaches.

ABSTRACT: Highly multiplexed imaging assays allow simultaneous quantification of multiple protein and phosphorylation markers, providing a static snapshots of cell types and states. Pseudo-time techniques can transform these static snapshots of unsynchronized cells into dynamic trajectories, enabling the study of dynamic processes such as development trajectories and the cell cycle. Such ordering also enables training of mathematical models on these data, but technical challenges have hitherto made it difficult to integrate multiple experimental conditions, limiting the predictive power and insights these models can generate. In this work, we propose data processing and model training approaches for integrating multiplexed, multi-condition immunofluorescence data with mathematical modelling. We devi

SUBMITTER: Cortes-Rios J 

PROVIDER: S-EPMC12520361 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature