M. D. Leiserson

The paper develops a computational pipeline to identify microbial reads in scRNA-seq data and finds that microbial reads are enriched in myeloid cells with proinflammatory transcriptional changes.

The paper identifies p53, KRAS, and VHL mutations as being selected during CRISPR-Cas9 editing through computational and experimental analysis.

This paper develops a multifactorial model to predict T cell expansion and clinical benefit from PD-L1 inhibitors using clinical, tumor, and circulating features, showing improved accuracy over single biomarkers.