COURSE CURRICULUM

The M.S. in Bioinformatics program is designed to prepare students for careers in data-intensive fields such as biotechnology, pharmaceuticals, agriculture, environmental science, and biomanufacturing by combining strong computational training with modern biological science. The program emphasizes practical, career-relevant skills rather than a traditional thesis-only model, allowing students to build expertise in genomics, programming, and applied data analysis while also gaining industry exposure through a structured capstone experience. Core coursework provides a foundation in genomics and computational biology, including GEN 811 Genomics and Bioinformatics, where students learn how biological data is generated and interpreted at large scales; GEN 812 Programming for Bioinformatics, which develops essential coding and algorithmic skills for analyzing biological datasets; ANFS 933 Design, Analysis, and Interpretation of Experiments, which trains students in experimental design and statistical reasoning; and MCBS 913 Applied Bioinformatics, which integrates biological concepts with computational tools used in real-world research and industry settings. Beyond these required courses, students work closely with faculty advisors and admissions committees to create a personalized academic plan that aligns with individual career goals, selecting electives from areas such as population genetics, human genetics, molecular evolution, comparative genomics, and protein structure and function. This flexibility allows students to specialize in fields like genetic engineering, protein biochemistry, or cell-based imaging while also exploring interdisciplinary electives in bioengineering, entrepreneurship, business, and regulatory science, including intellectual property and biotechnology law. A key component of the degree is the capstone experience, which can take the form of a research project in a university laboratory, an industry internship, or a structured applied training program, often involving collaboration between academic and professional supervisors. Students typically complete two semesters of independent bioinformatics research and present their findings at a graduate research conference, ensuring they graduate with both technical expertise and practical, real-world experience that supports immediate entry into advanced scientific or industry roles.