Daylin Morgan

The paper uses cell barcoding to show that hiPSC lineages have different differentiation outcomes into cardiomyocytes, highlighting lineage-dependent variability in cardiac differentiation.

This study uses deep learning to classify transcriptomic subpopulations in breast cancer cell lines based on morphology, showing that chemotherapy-induced changes and intra-line subpopulations are identifiable.

This study uses lineage tracing and scRNA-seq to analyze clone-specific responses to doxorubicin in triple-negative breast cancer, finding no pre-existing resistance and divergent treatment responses.

The paper introduces CMDuo, a tool to map cell-cell fusion events in tumors using scRNA-seq, revealing subclonal transcriptomic hybrids and fusion-driven cell states in triple-negative breast cancer.

The paper introduces clusterCleaver, a computational tool that identifies surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations using scRNA-seq data.