Dr. Li's research focuses on gene-environment interactions in cardiometabolic disease and chronic kidney disease (CKD), providing crucial insights for precision health. 

Our lab focuses on developing methods, platforms, and infrastructure for the integration and analysis of multimodal healthcare and biomedical data to address important clinical questions.

The Ruan Lab focuses its research on developing statistical methods and computational algorithms for multi-omics data with applications in complex human diseases.

We are interested in taking bioinformatics and data integration approaches to gain insights into cancer metabolism, inborn errors of metabolism, and lung neoplasm.

The lab focuses on developing bioinformatics algorithms and deep learning models to identify new disease genes and therapeutic targets for human diseases, as well as development and maintenance of data management system for genomic and clinical databases.

I am interested in developing computational models and algorithms for big data to predict patients' outcomes, which can help clinicians to tailor treatment plans for individual patients.

Our team is interested in developing computational models to predict patient outcomes, which will allow clinicians to tailor treatment plans for individual patients.

Our research revolves around using state-of-the-art bioinformatics and biostatistics approaches to study the implications of tumor immunology for tumorigenesis, metastasis, prognosis, and treatment response in a variety of cancers.

Dr. Bedimo studies strategies for optimally managing drug-resistant HIV patients, analyzing metabolic abnormalities in HIV patients, and studying the effects of HCV co-infection. 

Dr. Vega and co-workers have discovered three other causes of high LDL. First, she found that some patients have abnormal LDL particles that cannot be removed from circulation because the abnormal LDL does not recognize the receptors.