Clinical Research Informatics
Clinical Research Informatics Application Track teaches knowledge, theories, and skills needed to accelerate the generation of new knowledge across the translational research spectrum and to perform research in precision medicine. Students are required to demonstrate competency in (a) informatics methods required for utilizing biomedical data for research, (b) methods for data collection, integration, modeling, and quality, as well as for streamlining analytic processes, development of infrastructure, and decision support for research, (c) developing novel computational methods for information extraction, retrieval, and knowledge discovery as applicable to research (e.g. phenotyping), and (d) developing novel informatics methods that advance the practice of research (e.g., recruitment, reproducibility of research).
Special Interest Groups
Ph.D. students are required to attend at least one SIG (all students are encouraged), which bring people with similar interests together to learn, share, and experiment.
- Translational Bioinformatics SIG
- Computational SIG
Sign up for at least one practicum to gain hands-on experience and work with a team on a project.
Global Health Informatics
This is a hands-on, project based course with interdisciplinary experience in informatics activities in global health projects or resource-limited organizations and agencies. Integration of informatics content, skills, and role expectations is emphasized. Students will collaborate with global health partners in multi-disciplinary teams and synthesize informatics course content and apply to actual project/ site issues. Students interested in applying informatics methods or developing informatics methods for global health problems will find this of interest.
Please contact Ram Gouripeddi for more information.
Review and discuss literature in this area.
The Translational Bioinformatics SIG hosts a combination of journal club and student research in progress presentations.
Feel free to meet individually with faculty and/or to attend their weekly lab meetings.
Samir Abdelrahman; Mollie Cummins, Nursing Informatics; Michael Dean, Pediatrics; Karen Eilbeck; Julio Facelli; Ram Gouripeddi; Bernie LaSalle; Younghee Lee; Gang Luo; Stephane Meystre; Alan Morris, Intermountain; Scott Narus, Intermountain; Flory Nkoy, Pediatrics; Matthew Samore, Epidemiology; Brian Sauer, Epidemiology; Katherine Sward, Nursing Informatics.
Tom Greene, Population Health Sciences; Rachel Hess, Population Health Sciences.