Ansam F. Sinjab

The paper develops DeMixNB, a deconvolution model for sparse-count RNA sequencing data, showing its utility in analyzing tumor cell plasticity in breast and lung cancer.

METI integrates spatial transcriptomics and cell morphology to improve analysis of tumor microenvironments, showing consistent performance across multiple cancer types.

The paper analyzes single-cell RNA-seq data to identify ACE2 expression patterns in human lung epithelial cells, finding high ACE2 expression in alveolar type II cells and co-expression with pathogen receptors.