Bioinformatics BS

4 Years On Campus Bachelors Program

University of Utah

Program Overview

The Bioinformatics BS at the University of Utah combines mathematics, biology, computer science and data science to prepare students to solve complex problems involving biological and health-related data. It is particularly well suited to students interested in genomics, biotechnology, biomedical research, health science and computational problem-solving, with opportunities to develop programming, statistical and biological expertise through an interdisciplinary curriculum.

Curriculum Structure

Year 1: Students establish the scientific and quantitative foundation of the degree through courses such as BIOL 1610 – Fundamental Principles of Biology I: Cells, Genetics, and Biochemistry, MATH 1210 – Calculus I, and CHEM 1210 – General Chemistry I. SCI 1500 – Interdisciplinary Principles of Scientific Inquiry also introduces students to interdisciplinary scientific thinking, while the program highlights first-year hands-on research opportunities through the Science Research Initiative.

Year 2: Students build on their biological and mathematical foundation by moving further into quantitative analysis, computing and biological data. The curriculum develops the combination of mathematics, statistics, biology and computer science that forms the core of bioinformatics, with students progressing toward computational approaches to biological problems.

Year 3: Students begin applying their knowledge more directly to biological datasets and computational research. Courses such as BIOL 3715 – Bio Data Analysis and Visualization provide hands-on experience with biological data management, statistical analysis and visualization using modern open scripting tools such as R or Python, including datasets from genomics, ecology and physiology.

Year 4: Students bring together their mathematics, biology and programming skills to address more advanced bioinformatics and health-science problems. By completion, students are expected to demonstrate proficiency in Python, apply statistics and data science within bioinformatics frameworks, collaborate effectively, and complete an experiential learning, internship or career-exploration opportunity.

Focus areas

Bioinformatics, computational biology, genomics, biological data analysis, data science, statistics, Python programming, machine learning for genetics, biological data mining, biomedical research, health science data and biotechnology.

Learning outcomes

Students develop the ability to apply mathematical, statistical and data-science principles to bioinformatics; understand biology and chemistry relevant to health-science data; use Python and other computational tools; communicate and collaborate effectively; and complete an experiential learning or internship/career-exploration experience.

Professional alignment (accreditation)

The Bioinformatics BS is an interdisciplinary program housed in the University of Utah's Department of Mathematics. The University of Utah is institutionally accredited by the Northwest Commission on Colleges and Universities (NWCCU); I did not find evidence on the official program pages of a separate specialized professional accreditation specifically for the Bioinformatics BS.

Reputation (employability rankings)

The University of Utah describes itself as an R1 university and highlights access to nationally ranked biomedical, health sciences and genomics programs. The university also describes bioinformatics as a rapidly growing field with opportunities across biotechnology, pharmaceuticals, healthcare and research, while its UGuide career data shows strong earning potential for related careers such as bioinformatics scientist and biostatistician.

Experiential Learning (Research, Projects, Internships etc.)

The Bioinformatics BS is designed to connect classroom learning with real biological and computational problems. Students can gain practical experience through first-year research with the Science Research Initiative, biological data analysis and visualization, internships with industry partners, and career-focused experiential learning; the program specifically requires students to complete an experiential learning or internship/career-exploration opportunity during the degree.

The University of Utah also provides access to research infrastructure relevant to biological and computational work, including DNA sequencing resources and university-wide health-science core facilities. Key opportunities include:

Science Research Initiative (SRI): Bioinformatics students can participate in hands-on research experiences beginning in their first year, giving them early exposure to university research.
Biological data analysis: BIOL 3715 – Bio Data Analysis and Visualization provides hands-on experience managing, exploring, analyzing and visualizing biological datasets, with R and Python used as modern open scripting tools.
Python programming: Python is specifically identified as a programming platform students are expected to master for use in academic and professional settings.
DNA Sequencing Facility: The School of Biological Sciences has an Illumina MiSeq high-throughput DNA sequencing device and an Agilent Tapestation for sequencing-library quality control, providing relevant infrastructure for experimental biological research.
Research core facilities: University of Utah Health maintains a broad network of research cores and services, including facilities related to genetic science, metabolomics and lipidomics, mutation generation and detection, and protein-metabolite discovery.
Industry and internship experience: The university specifically identifies internship opportunities with industry partners in biotechnology and health technology as an advantage of the Bioinformatics BS.
Career-focused projects: U Career Success also offers Crimson Projects, where students collaborate with industry professionals, use modern technologies and AI tools, and deliver outcomes for organizations.

Progression & Future Opportunities

The Bioinformatics BS can prepare graduates for roles that combine biological knowledge with computational and quantitative skills across biotechnology, healthcare, pharmaceuticals and research. University of Utah career information identifies pathways such as bioinformatics scientist, bioinformatics technician, biostatistician and biologist, while also noting that many advanced research positions require graduate-level study.

Typical career roles include: Bioinformatics Scientist, Bioinformatics Technician, Biostatistician, Biologist

Career and academic advising: Bioinformatics BS advisors help students with course selection, degree planning, career exploration and connecting with opportunities in the field. U Career Success also provides career coaching covering career exploration, resumes, internships, interviews and job searching.
Employment and salary potential: University of Utah UGuide reports a 2025 median annual salary of approximately $93,000 for bioinformatics scientists, with an estimated range of $54,000–$162,000. For bioinformatics technicians, the reported 2025 median is approximately $71,000, with an estimated range of $40,000–$155,000. These are national labor-market estimates rather than University of Utah graduate salary figures.
Biostatistics pathway: UGuide reports a 2025 median annual salary of approximately $103,000 for biostatisticians, with an estimated range of $60,000–$172,000.
University–industry connections: The Bioinformatics BS specifically highlights internship opportunities with industry partners in biotechnology and health technology, helping students connect their academic preparation with professional environments.
Research progression: Students can build on undergraduate research experience and the university's strengths in genomics, systems biology and biomedical informatics, creating a foundation for research-oriented graduate study.
Long-term accreditation value: The University of Utah's institutional NWCCU accreditation provides recognition that the university meets established standards of educational quality and effectiveness. No separate specialized accreditation was identified for this Bioinformatics BS.

Further Academic Progression: Graduates can continue into master's or doctoral-level study in areas such as bioinformatics, computational biology, biomedical informatics, data science, biology, biostatistics or related biomedical and life-science disciplines. For research-intensive careers, the University of Utah's career guidance notes that advanced positions commonly require a master's degree or PhD, making graduate study a natural progression for students interested in research and advanced computational biology.