Bevan Emma Huang

Machine learning-based proteogenomic data modeling identifies circulating plasma biomarkers for early detection of lung cancer

This study uses machine learning to model proteogenomic data and identifies plasma biomarkers for early lung cancer detection, achieving AUCs of 0.78-0.88 in predicting diagnosis up to 9 years before symptoms.

Simultaneous immunomodulation and epithelial-to-mesenchymal transition drives lung adenocarcinoma progression

This study profiles early-stage lung adenocarcinoma using multiplexed imaging mass cytometry to reveal two progression pathways: inflammation-driven and fibrosis-driven, with EMT masking malignant cell expansion.

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome

A multi-parent advanced generation inter-cross population for genetic analysis of multiple traits in cowpea (Vigna unguiculata L. Walp.)

The paper develops a MAGIC population for cowpea to dissect genetic traits and improve breeding, identifying trait-associated SNPs and recombination patterns.