Computational Biology, Minor College of Engineering
The minor in Computational Biology will provide to students with engineering, physical science or biological science majors the foundations necessary to build efficient computational models and algorithms, use state-of-the-art techniques for scientific analysis and create scalable infrastructure environments for biological and biotechnological applications.
More information can be found at Computer Science Minors.
Minor Advisors
Faculty Advisors
V. Filkov, P. Koehl, I. Tagkopoulos
Academic Advisors
J. Clifford, K. Gage, M. Ramirez, P. Kumari
Students must take a total of 20 upper-division units, with two required courses and 12 units of upper-division electives, as specified below. A minimum GPA of 2.000 is required for coursework in the minor. Students should note that most of the courses listed below have lower-division prerequisites. No more than one course of upper-division work will be permitted for overlap between any major and the minor.
| Code | Title | Units |
|---|---|---|
| Required Courses | ||
| Choose one algorithms course: | 4 | |
| Algorithms for Data Science | ||
| Algorithm Design & Analysis | ||
| Choose one bioinformatics course: | 4 | |
| Theory & Practice of Bioinformatics | ||
| Computational Structural Bioinformatics | ||
| Electives | ||
| Choose a minimum of 12 units: | 12 | |
| Modeling Strategies for Biomedical Engineering | ||
| Genes & Gene Expression | ||
or BIS 101V | Genes & Gene Expression | |
| Cell Biology | ||
| Population Biology & Ecology | ||
| Applied Bioinformatics | ||
| Applied Machine Learning for Non-Majors | ||
or ECS 171 | Machine Learning | |
| Databases for Non-Majors | ||
or ECS 165A | Database Systems | |
| Algorithms for Data Science 1 | ||
| Algorithm Design & Analysis 1 | ||
| Theory & Practice of Bioinformatics 1 | ||
| Computational Structural Bioinformatics 1 | ||
| Scientific Computation | ||
| Probability & Statistical Modeling for Computer Science | ||
| Programming Languages | ||
| Scripting Languages & Their Applications | ||
| Programming on Parallel Architectures | ||
| Software Engineering | ||
| Introduction to Artificial Intelligence | ||
| Scientific Visualization | ||
| Introduction to Evolution | ||
| Introduction to Ecology | ||
| Population & Quantitative Genetics | ||
| Phylogeny, Speciation & Macroevolution | ||
| Human Genetic Variation & Evolution | ||
| Advanced Molecular Biology | ||
| Macromolecular Structure & Function | ||
| Principles of Genomics | ||
| Mathematical Statistics: Brief Course | ||
| Fundamentals of Statistical Data Science | ||
| Data & Web Technologies for Data Analysis | ||
| Big Data & High Performance Statistical Computing | ||
| Total Units | 20 | |
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No course can count as both a required course and an elective in the minor.