Ph.D. University of Pittsburgh
The main focus of our research has been to develop computational strategies and algorithms for analysis, especially on large-scales, of biological data to extract knowledge and generate hypotheses. Over the years we have developed several bioinformatics tools, such as those for comparing protein structures, protein-protein docking, and ligand binding site prediction. We have also developed network-based approaches to study nature’s design of protein architecture and its evolution, and to understand the design principles of biological circuits. In recent years, we have collaborated with physicians using patient data from local hospitals to develop artificial intelligence (AI) tools for medical applications. Two completed projects are: 1) identification of a handful of circulating miRNA as liquid biopsy biomarkers for detecting and classifying six major cancers; 2) electrocardiogram-based detection of cardiac diseases such as arrhythmias and pulmonary hypertension. These AI tools are currently being implemented to test their prediction effectiveness in real-world clinical settings. In the future, we will continue the AI research, on additional diseases such as sleep apnea, and on biomedicine problems such as drug discovery.
Detection and Classification of Cardiac Arrhythmias by a Challenge-Best Deep Learning Neural Network ModeliScience, Mar 27, 2020
Risk stratification for lung adenocarcinoma on EGFR and TP53 mutation status, chemotherapy, and PD‐L1 immunotherapyCancer Medicine, Aug 13, 2019