Using and developing tools and techniques in areas such as artificial intelligence and machine learning alongside technologies such as cloud computing, the DBMI faculty bring excellence in one or more domains of informatics including genomics and computational biology, translational bioinformatics and personalized medicine, clinical research informatics, and clinical informatics, while developing tools and methods such as ontologies, knowledge engineering, machine learning and artificial intelligence to bear on biomedical challenges.
The DBMI faculty use approaches of genome-scale biology, multiscale modeling, simulation, data integration, and mathematical and predictive analytics to marry disparate but related aspects of the campus’s clinical and research portfolios to advance knowledge and improve healthcare. Many of our faculty are affiliated with the Colorado Center for Personalized Medicine and Center for Health AI.
Albers Lab Researchers in the Albers Lab focus on advancing biomedicine using data assimilation of both clinician and patient collected data to forecast physiology and compute new phenotypes, health care process modeling and analysis, and more. | Bennett Lab Researchers in the Bennett Lab focus on clinical decision-making in high-risk environments such as intensive care units and on the development and implementation of informatics and data science methods and tools to improve outcomes. | Claw Lab
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Researchers in the Cole Lab intersect large-scale genomics and nutrition data to learn more about diet's role in the body and in human health, with a focus on cardiometabolic disease. | Dashnow Lab
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Dwork Lab | Gignoux Lab | Researchers in the Greene Lab are dedicated to answering important questions in biology and medicine with computation. They focus on bringing together publicly available big data, developing new computational methods to analyze that data, and creating tools to put those resources into the hands of every biologist.
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Hendricks Lab | Johnson Lab
| JRavi Lab |
Julian Lab | Researchers in the Krishnan Lab develop computational approaches that take advantage of massive public data collections to build predictive and interpretable models of genes, molecular networks, and tissue mechanisms that underlie the heterogeneity of complex diseases. | Ethan Lange Lab |
LARK Lab | Leslie Lange Lab Researchers in Dr. Leslie Lange’s Lab focus on the genetic epidemiology of complex traits, primarily regarding cardiovascular disease, obesity, diabetes and pulmonary related phenotypes. Particular areas of focus include genetics studies in understudied minorities and facilitating large multi-study genetic collaborations. | Lozupone Lab |
Norman Lab
| Pozdeyev Lab | Researchers in the Sirlanci Lab focus on investigating problems arising in biomedicine by using data assimilation techniques. For this purpose, the lab uses both physiology-based mechanistic models and machine learning type of models. |
Stanislawski Lab | Researchers in the Stranger Lab study human genetics, bioinformatics, statistical analysis of multidimensional data, and cutting-edge computer science to unravel the complexities of health and disease. They develop methods to identify and interpret context-specific genetic effects and advance discoveries on the impact of sex and gender on the genetics of complex traits. | The mission of the Way Lab is to integrate high-dimensional biomedical data science into clinical decision-making to improve patient outcomes. They will develop new methods, approaches, assays, and software for analyzing high-dimensional genomic, molecular, and morphological data. |
Wiley Lab | Yang Lab |