Geoffrey Lowell Chupp

The paper identifies cell types regulated by circulating miRNAs linked to asthma exacerbations using scRNA-seq and validates findings in GEO datasets.

This paper shows biologic therapy in severe asthma reduces a specific activated eosinophil subpopulation linked to worse asthma control and lung function.

This study uses single-cell RNA sequencing to analyze sputum cells from asthma patients and controls, identifying dysregulated pathways and communication networks involved in asthma pathogenesis.

iDESC identifies differential expression in scRNA-seq data with multiple subjects by separating subject effects from disease effects, showing better performance than existing methods.

The paper identifies gene signatures predictive of asthma severity using a denoising autoencoder and random forest classifier applied to sputum gene expression data.

The paper integrates heterogeneous RNA-seq data from asthmatic patients to uncover gene-microbe interactions and their clinical associations.