Bachelor of Science Bioinformatics

4 Years On Campus Bachelors Program

University of Arizona

Program Overview

The Bachelor of Science in Bioinformatics at the University of Arizona brings together biology, computer science, mathematics, and data analysis to help students understand and work with the large amounts of biological data used in modern research. It is a strong choice for students who enjoy both life sciences and computing and want to explore areas such as computational biology, genomics, biotechnology, biomedical research, and data science.

Curriculum Structure

Year 1: Students begin by building a solid foundation in biology, chemistry, mathematics, and computing through courses such as MCB 181R/181L Introductory Biology I, CHEM 141/145 General Chemistry I, MATH 122A/B Calculus I, and ISTA 130 Computational Thinking and Doing. Courses such as ISTA 116 Statistical Foundations for the Information Age also introduce students to the statistical and analytical skills needed to work with biological data.

Year 2: Students strengthen their understanding of biological and chemical sciences through courses such as ECOL 182R/182L Introductory Biology II, CHEM 241A/243A Organic Chemistry I, and CHEM 241B/243B Organic Chemistry II. They also develop their quantitative skills through MATH 263 Biostatistics, learning how statistical methods can be used to understand and interpret scientific data.

Year 3: Students move further into specialized bioinformatics study through courses such as ECOL 296B Seminar in Bioinformatics, ECOL 320 Genetics, ECOL 335 Evolutionary Biology, and ECOL 346 Bioinformatics. Courses such as ISTA 320 Applied Data Visualization and ISTA 321 Data Mining and Discovery help students develop practical skills for analyzing complex datasets and presenting their findings clearly.

Year 4: In their final year, students can use upper-division electives to shape their studies around their academic and career interests. Options can include ISTA 322 Data Engineering, MCB 411 Molecular Biology, IMB 406 Human Immunology, ECOL 430 Conservation Genetics, and NETV 379 Cloud Computing, giving students opportunities to develop a more specialized combination of biological and computational skills.

Focus Areas

Bioinformatics, Computational Biology, Biological Data Analysis, Data Science, Genetics, Evolutionary Biology, Biostatistics, Data Visualization, Data Mining, Data Engineering, Computer Science, Programming, Biological Information Management, Biomedical Informatics, Biotechnology, Software Development, Genomics

Learning Outcomes

Students develop the ability to combine biological knowledge with computational approaches to manage, analyze, interpret, and communicate complex biological information. The program also builds skills in data analysis, programming, data management, research, problem-solving, critical thinking, systems analysis, and scientific communication.

Professional Alignment (Accreditation)

The B.S. in Bioinformatics is an interdisciplinary science degree, and the University of Arizona does not identify a specific professional accreditation for this program. Instead, the curriculum focuses on developing the combination of biological and computational skills needed for modern bioinformatics, computational biology, biotechnology, and data-driven research.

Reputation (Employability Rankings)

The University of Arizona describes its B.S. in Bioinformatics as one of the first undergraduate bioinformatics degree programs in the United States, reflecting the university's early involvement in this growing field. The program prepares students for opportunities where biology and computing come together, including biomedical informatics, pharmaceutical development, clinical research, biotechnology, data analysis, database development, and software development.

Experiential Learning (Research, Projects, Internships etc.)

The B.S. in Bioinformatics at the University of Arizona gives students plenty of opportunities to put their knowledge into practice by combining biology, computer science, statistics, and data analysis. Through research projects, hands-on coursework, faculty-led research, and industry-focused learning, students can develop practical skills while working with real biological and computational data.

Students can gain practical experience through:

Course-based research: Students can work on authentic research questions through course-based undergraduate research experiences, where they collect, analyze, and interpret data while developing research and problem-solving skills.
Faculty-led research teams: Through the Vertically Integrated Projects program, students can join faculty-led research teams, collaborate with students from different disciplines, earn academic credit, and contribute to research projects over multiple semesters.
Independent research: Students can work with faculty mentors on individual research projects and develop research proposals that may lead to a paper, poster, or presentation.
Bioinformatics data analysis: Courses such as ECOL 346 Bioinformatics provide practical experience working with complex biological datasets, including next-generation biological data. Students develop skills in the Unix command line and Python scripting while learning how to combine information from different sources to investigate biological questions.
Data visualization and mining: ISTA 320 Applied Data Visualization helps students learn how to communicate complex datasets effectively, while ISTA 321 Data Mining and Discovery introduces techniques such as classification, cluster analysis, association rule analysis, and anomaly detection.
Data engineering: Students who take ISTA 322 Data Engineering gain experience with industry-standard approaches for managing, storing, manipulating, and preparing large datasets for scientists and decision-makers.
Bioinformatics seminars: ECOL 296B Seminar in Bioinformatics introduces students to current developments in the field through presentations from University of Arizona faculty working in bioinformatics and computational biology, as well as scientists from the biotechnology industry.
Genomic data analysis: Through relevant advanced courses such as MCB 416A Bioinformatics and Functional Genomic Analysis, students can gain hands-on experience analyzing high-throughput genomic data using R-based open-source software and Bioconductor.
Health informatics research: Students may also have opportunities to participate in health informatics and biomedical research projects, applying data science and informatics approaches to real-world health-related questions.
Internships and career experience: Students can explore research positions, internships, employment opportunities, and professional networking opportunities through University of Arizona career and research resources.

Overall, the program provides a strong balance of biological knowledge and computational practice, helping students become comfortable working with real datasets, programming tools, research methods, and interdisciplinary teams.

Progression & Future Opportunities

The B.S. in Bioinformatics at the University of Arizona prepares students for careers that bring together biology, computing, statistics, and data analysis. Graduates can apply these skills across biotechnology, healthcare, biomedical research, pharmaceutical development, data science, and software-related fields, while also having a strong foundation for further academic study.

Typical job roles include: Bioinformatics Scientist, Bioinformatics Analyst, Data Scientist, Clinical Data Manager

Students can benefit from a range of career and professional opportunities as they prepare for life after graduation:

Career guidance and employment support: University of Arizona Career Services helps students prepare for employment through career coaching, job-search support, networking opportunities, and access to Handshake. College of Science students can also receive individual career guidance through dedicated career coaching.
Career-related experience: The University encourages students to gain experience through internships, research, part-time employment, leadership activities, volunteering, study abroad, and co-op opportunities. These experiences can help students build practical skills and strengthen their resumes before graduation.
Employment and salary outcomes: University-wide graduate outcome data provides information on graduates' destinations and earnings. For University of Arizona undergraduate alumni overall, reported median wages are about $48,400 during the first year after graduation, increasing to approximately $98,800 after 30 years. These figures represent university-wide undergraduate alumni and are not specific to Bioinformatics graduates.
Industry exposure: Through ECOL 296B: Seminar in Bioinformatics, students can hear directly from biotechnology industry scientists as well as University of Arizona faculty involved in bioinformatics and computational biology research. This helps students understand current developments and career opportunities within the field.
Interdisciplinary opportunities: Bioinformatics students can benefit from the University's broad research environment, with EEB faculty collaborating across many areas of the university. This can expose students to applications of bioinformatics in fields such as medicine, agriculture, environmental science, and other biological disciplines.
Preparation for advanced careers: The combination of biological sciences, programming, data management, statistics, and computational analysis gives graduates a versatile skill set that can be applied to a wide range of roles in research, biotechnology, healthcare, and data-driven industries.
Accreditation and long-term value: The University of Arizona does not list a separate professional accreditation specifically for the B.S. in Bioinformatics. The degree's long-term value comes from its interdisciplinary curriculum, which combines biological science with computational and data-focused skills that remain relevant across several growing sectors.

Further Academic Progression: After completing the B.S. in Bioinformatics, students can continue their education through master's or doctoral programs in areas such as bioinformatics, computational biology, genomics, biotechnology, data science, biostatistics, biomedical sciences, and related disciplines. Students interested in research can progress toward advanced research degrees, while those seeking specialized professional careers can pursue postgraduate programs that build on their biological, computational, and analytical background.