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.
Dr. David Albers’s lab focuses 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.
Dr. Bennett’s group focuses 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.
Research in the Claw Lab focuses broadly on personalizing medicine, using genetic information and biomarkers for tailored treatment, in relation to pharmacogenomics as well as understanding the ethical, cultural, and social implications of genomic research with population.
The Cole Lab intersects 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.
Research in the Davis Lab focuses on technologies for data integration and reuse.
Research in the Dwork Lab focuses on small data exploitation for computational imaging and radiation oncology. Applications include medical image reconstruction, image quantitation, radiation treatment planning, and inexpensive medical devices.
The Gignoux Lab, a member of the Colorado Center for Personalized Medicine, works at the interface of statistical and population genetics to improve our understanding of complex traits.
The Greene Lab is a team of researchers dedicated to answering important questions in biology and medicine with computation. We 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.
Dr. Hendricks' research spans a variety of health and disease projects including work in large scale genetic, methylation, metabolomic, and expression studies as well as more focused functional and model organism research. Recent applied and collaborative projects include understanding the mechanisms and mediators behind successful nutrition interventions in children and adults.
More information will be available soon.
Dr. Krishnan's group develops 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
The Lozupone Lab focuses on factors that shape human microbiota composition in health and disease and to elucidate the functional consequences of compositional differences, both in terms of the biological/metabolic properties of individual bacteria and host interactions.
Research in the Norman Lab focuses on immunogenetics, which is the genetic variation that underpins our differential responses to infection and autoimmunity. In particular, the lab studies the co-evolution of HLA molecules that are expressed by most healthy cells, and the Natural Kill (NK) cell receptors that interact with HLA to control the immune response.
|Research in the Sirlanci Lab focuses on investigating problems arising in biomedicine by using data assimilation techniques. For this purpose, she uses both physiology-based mechanistic models and machine learning type of models.
Dr. Stanislawski’s lab studies the molecular epidemiology of cardiometabolic disease, obesity, and other inflammatory conditions, particularly the role of the microbiome and its interactions with other omic profiles in diverse human populations. The lab also investigates how omic profiles relate to responsiveness during weight loss and exercise interventions.
The mission of our lab is to integrate high-dimensional biomedical data science into clinical decision making to improve patient outcomes. We will develop new methods, approaches, assays, and software for analyzing high-dimensional genomic, molecular and morphological data.
Research in the Yang Lab focuses on epigenetic regulation and transcriptional profiles in pulmonary fibrosis, sarcoidosis and asthma