M. E. Burkard

This paper evaluates CIN measures across mechanistic models, finding that single-cell methods like scDNAseq outperform bulk methods and proposes a standardized unit for CIN measurement.

The paper evaluates individual patient-derived cancer organoids using optical metabolic imaging to predict therapeutic response and identify subclonal populations and resistance mechanisms.

This paper develops a framework to quantify chromosomal instability using agent-based modeling and Bayesian inference, validated with experimental data and applied to clinical samples.