Dr. Shen’s research focuses two areas: i) computational and statistical modeling of high-throughput proteomics data including mass spectrometry based protein identification and protein-protein interactions to improve the accuracy of the interpretation and reliability of the false positive control/estimate; ii) statistical models that integrate various sources of OMICS data and their uncertainty to study molecular and cellular pathways.