Computational Biology - Minor

Computational biology is an interdisciplinary field that develops and applies computational methods to understand biological systems and address societal challenges.

The computational biology minor is a cross-college minor that welcomes students from a diversity of majors. Students come together from disciplines in biology, math, computer science and engineering in interdisciplinary learning settings. The minor curriculum is intentionally designed to provide students overlap with their respective computational and biological expertise while challenging students to integrate core concepts and skills.

The minor teaches students to combine computational thinking and algorithms to tackle complex biological systems and topics like epidemiology, biotechnology, precision medicine & human health, genetics & genomics, environmental systems and scientific research. Students learn:

• Computational biology core concepts and experimental techniques.
• Representing and understanding biological data and patterns.
• Biologically relevant skills in applied math, data science and statistics, and computing.
• Modeling and predicting biological processes and dynamics.
• Biological phenomena under uncertainty with probabilistic and statistical analyses.

Visit the Computational Biology Minor webpage for the most recent information.

Requirements

A prerequisite is Calculus I or equivalent with a C- or better such as provided by MATH 1300/MATH 1310/APPM 1345/APPM 1350. Students must have a minimum cumulative GPA of 2.500 to declare this minor. Students interested in declaring should visit the Computational Biology Minor webpage and submit an interest form. A cumulative GPA of 2.000 or better is required in the courses that are used to satisfy the minor. Each individual course that is used to satisfy the minor must be passed with a C- or better.

Required Courses and Credits

The minor is divided into three course areas: Skills, BioElectives, and Data & Structure + Bioprocesses. The common pathways through the minor are: a computing or math background, which fulfills most Skills coursework, or a biology background, which fulfills BioElective coursework. Data & Structure + Bioprocesses course offerings emphasize the integration of Skills and BioElective core concepts. Completion of 8 courses from the three course areas is required for the minor; courses may not double count to satisfy multiple minor requirements. Relevant coursework can be petitioned. Course lists are maintained on the Computational Biology Minor webpage.

Learning Outcomes

• Effectively identify and communicate Computational Biology topics and applications to specialists and non-specialists.
• Reframe and evaluate biological research questions in the context of computational theory and techniques.
• Contextualize data and modeling problems based on biological principles and the scientific discovery process.
• Collect and access biological data sources to study Computational Biology challenges.
• Evaluate methods of biological data collection, validation, extension, and reproducibility.
• Use and/or build computer-based systems, programs, and algorithms based in software design principles.
• Model structured biological data and systems using computational techniques.
• Predict and interpret biological phenomena under uncertainty with probabilistic and statistical analyses.