Course Requirements Overview
To obtain a minor in bioinformatics, students first complete background lower division courses in programming, biology and mathematics. Next, they build on this foundation with a Bioinformatics gateway seminar course and complete the Bioinformatics core curriculum, an upper division course on Algorithms, and one upper division elective course. Students are strongly encouraged to participate in undergraduate research as early as possible in one of the many research groups affiliated with UCLA Bioinformatics.
Fall 2020 information session slides:
Worksheet of required courses (last updated in spring 2019):
For more information, including official program requirements, please visit:
Bioinformatics Lower Division Required Courses
These four required courses are prerequisites for upper division courses.
- CS 32 or PIC 10C
- Lifesci 7A
- Math 33A
- Math 61
Students are required to take the two-unit gateway seminar course as early as possible.
CS 184 “Introduction to Computational Systems Biology” – Survey course designed to introduce students to computational and systems modeling and computation in biology and medicine, providing motivation, flavor, culture, and cutting-edge contributions in computational biosciences and aiming for more informed basis for focused studies by students with computational and systems biology interests. Presentations by individual UCLA researchers discussing their active computational and systems biology research.
Bioinformatics Core Curriculum
Students are required to take two of the three core Bioinformatics courses. However, we strongly recommend that students in the Bioinformatics Minor take all three.
- Computer Science CM 121 “Introduction to Bioinformatics” – Introduction to bioinformatics and methodologies, with emphasis on concepts and inventing new computational and statistical techniques to analyze biological data. Focus on sequence analysis and alignment algorithms.
- Computer Science CM 122 “Algorithms in Bioinformatics and Systems Biology” – Development and application of computational approaches to biological questions, with focus on formulating interdisciplinary problems as computational problems and then solving these problems using algorithmic techniques. Computational techniques include those from statistics and computer science.
- Computer Science CM 124 “Machine Learning Applications in Genetics” – Introduction to computational analysis of genetic variation and computational interdisciplinary research in genetics. Topics include introduction to genetics, identification of genes involved in disease, inferring human population history, technologies for obtaining genetic information, and genetic sequencing. Focus on formulating interdisciplinary problems as computational problems and then solving those problems using computational techniques from statistics and computer science.
In addition, students are required to take an upper division algorithms course, Computer Science 180, or Mathematics 182. This course provides an introduction to the design and analysis of algorithms.
Bioinformatics Upper Division Electives
Students take an elective course from a list of available courses:
- Computational and Systems Biology CM187 – “Research Communication in Computational and System Biology”
- Computer Science 170A – “Mathematical Modeling and Methods for Computer Science”
- Computer Science CM121 – “Introduction to Bioinformatics”
- Computer Science CM122 – “Algorithms in Bioinformatics and Systems Biology”
- Computer Science CM124 – “Machine Learning Applications in Genetics”
- Computer Science/Computational and Systems Biology CM186 – “Computational Systems Biology: Modeling and Simulation of Biological Systems”
- Ecology and Evolution 135 – “Population Genetics”
- Electrical Engineering 102 – “Systems and Signals”
- Electrical Engineering 141 – “Principles of Feedback Control”
- Human Genetics C144 – “Genomic Technologies”
- Molecular Cellular and Developmental Biology 144 – “Molecular Biology”
- Molecular Cellular and Developmental Biology 172 – “Genomics and Bioinformatics”
- Physiological Sciences 125 – “Molecular Systems Biology”
- Statistics 100A OR 100B – “Introduction to Mathematical Statistics” OR Civil and Environmental Engineering 110 – “Introduction to Probability and Statistics for Engineers” OR Electrical Engineering 131A – “Probability and Statistics OR Mathematics 170A – Probability Theory”
Official course descriptions can be found in the UCLA General Catalog here.
In addition, students with a Bioinformatics Minor may obtain credits for research with 8 units of Computer Science 194/199 or Bioinformatics 194/199, which can be used as additional electives to complete Minor requirements.
Contact a Bioinformatics undergraduate counselor via myUCLA Message Center. To make sure your message and request for a meeting reaches the appropriate counselor, please include the phrase “Bioinformatics Minor” in the subject line.