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Department of Biomedical and Health Informatics Laboratories
The scientific teams who work within DBHi laboratories use new methodological and technical approaches that advance science and interdisciplinary collaboration across a wide range of research topics. Ultimately, their goal is to contribute to high-quality, efficient healthcare that improves the diagnosis and treatment of children.
The Almasy Lab uses computational approaches to study genetic factors’ contribution to complex disorders’ etiology and neuropsychiatric phenotypes across the lifespan.
The Taylor Lab identifies treatments from complex biological network in silico models of metabolic disorders or disease, such as Leigh syndrome.
The Tsui Lab integrates healthcare and patient data to develop end-to-end, real-time decision support for direct impact to hospital staff, patients, and public health.
The Helbig Lab uses computational methods to understand the role of clinical and genetic factors in childhood epilepsies, facilitating precision medicine approaches.
The Tan Lab uses systems biology approaches to identify and characterize gene pathways underpinning tumorigenesis and normal development. The ultimate goal of the research in this laboratory is to use information from patient-specific, integrated gene networks to improve the diagnosis and treatment of cancer patients.
The Campbell Lab uses computational methods including natural language processing and other machine learning to improve the diagnosis and management of children with rare genetic disorders. One key interest of the laboratory is to integrate genetic information into patients’ electronic health records to provide real-time clinical decision support.