Charlie George Barker

MAGELLAN constructs interpretable computational models from pathway data and experimental rules, demonstrating predictive accuracy in breast cancer and NSCLC signalling.

This paper develops a molecular trajectory-based framework to model MASLD progression using transcriptomic and proteomic data, identifying novel biomarkers and mechanistic insights.

This study reveals how ARID1A-mediated transcriptional rewiring drives resistance to MAPK inhibitors in melanoma by altering signalling pathways, immune interactions, and receptor dynamics, highlighting potential targets for combinatorial therapies.

The paper uses single-cell RNA-sequencing to study heterogeneity in mouse gastruloids over time, revealing distinct mesodermal and neural differentiation trajectories and their implications for perturbation studies.

The paper integrates gene expression and cell shape imaging data to identify phenotype-specific gene networks and signaling pathways involved in breast cancer cell morphology.