Posts classified under: DBDS

Our laboratory uses machine learning in various clinical settings to predict and improve patients’ outcomes. This includes integrative “multiomics” analysis across genomics, proteomics, metabolomics, and single-cell technologies, as well as quantitative clinical phenotyping using wearable devices.

Research Areas: 

• Systems Biology
• Machine Learning
• Artificial Intelligence
• Multiomics Profiling
• Single Cell Biology
• Electronic Health Records
• Wearable Devices
• Maternal and Child Health
• Perioperative Care

The Witte Lab is a computational and epidemiological research group investigating the genetic and environmental contributions to disease risk and progression. We develop and apply novel genetic epidemiological methods to decipher the mechanisms underlying complex diseases. Current areas of research include the following: 1) Evaluating disease risk with novel approaches to polygenic risk scores and hierarchical models; 2) Assessing the shared genetic basis across different diseases and traits (pleiotropy); and 3) Finding genetic risk factors, improving screening, and reducing disparities in cancer.

Research Areas: 

• Bioinformatics
• Statistical Genetics
• Cancer Risk Prediction
• Genetic Epidemiology
• Epidemiology Methods