Application Track: Bioinformatics

Bioinformatics will help students develop skills in the application of bioinformatics and statistical genetics analysis, with a focus on translational studies and genomics. Weekly Research-in- Progress and Journal club are essential components of this track and students of all levels are expected to attend and present. Students are introduced to a wide range of bioinformatics and statistical genetics topics and gain hands-on experience with tools and data. Students must demonstrate competency in (a) understanding basic genetics and the nature of different types of genetic and phenotypic data, (b) design and implementation of algorithms to solve problems in genomic analysis, precision medicine, and translational research, (c) integration of computational genomics findings and statistical genetics analyses with medicine (translation) through integration with clinical decision support, database design, and human factors. Ultimately they will be able to specialize in large-scale genomic analysis, precision medicine, or translational research.

Recommended Course of Study

This is a recommended schedule for this track (numbers in parentheses indicate credit hours). Courses can be waived or tested out of with permission of the course instructor and the student's advisor. Ultimately, the courses a student takes should be determined and approved by the student and the graduate committee.

Grey = bridge course for those without background in genomics and medicine; light blue = DBMI core course; dark blue = DBMI course for this track; white = electives and research hours.

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Recommended Electives

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Special Interest Groups

PhD 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.

Practicum

Sign up for at least one practicum to gain hands-on experience and work with a team on a project.

Students are encouraged to develop a practicum with a faculty member for a semester, including faculty members outside of DBMI.

Affiliated Faculty

Feel free to meet individually with faculty and/or to attend their weekly lab meetings.

DBMI

Samir Abdelrahman; Karen Eilbeck; Julio Facelli; Younghee Lee; Aaron Quinlan DBMI and Human Genetics.

Non-DBMI:

Brian Chapman, Radiology; Laura Heermann-Langford, Intermountain, NI; Rachel Hess, Population Health Sciences; Rashmee Shah, Cardiology.

Ph. D. Application Deadlines

Fall Semester

Domestic: December 31st

International: December 1st

Online Application

Biomedical Informatics at the University of Utah