Bethany R. Jebson

This paper compares methods for imputing cell-type specific expression from mixed RNA-seq data, finding that machine learning methods like LASSO and ridge outperform domain-specific methods in recovering differential gene expression.

The paper develops a Treg gene and protein signature to predict disease activity in Juvenile Idiopathic Arthritis using machine learning and flow cytometry.

This study uses spectral flow cytometry to characterize the immune landscape of inflamed joints in JIA, identifying site-specific immune cell phenotypes and potential therapeutic targets.