IMPORTANT: CasB is currently in the process of revising the concentration requirements into tracks. We expect the Bioinformatics track to be officially approved and go live effective Winter 2022, pending final approval from the University.

The Bioinformatics track is designed for students interested in computational discovery and management of biological data, primarily genomic, proteomic, or metabolomic data. Bioinformatics emphasizes computational, statistical, and other mathematical approaches for mining, modeling, and analyzing high-throughput biological data and the inherent structure of biological information. Example research problems include finding statistical patterns that reveal genomic or evolutionary or developmental information, studying how regulatory sequences give rise to programs of gene expression, or researching how the genome encodes the capabilities of the human mind.

Track Curriculum

Bioinformatics Track Requirements (effective 22 Winter, pending final approval from the University): 5 upper division courses

1 Course from COM SCI CM121; COM SCI CM122; COM SCI CM124

2 Courses from COM SCI CM121; COM SCI CM122; COM SCI CM124; EE BIOL C135; MCD BIO CM156; MCD BIO 187AL; PHYSCI 125; STATS M254

2 Courses from list of Life Science courses (see below)

Life Science Courses (select any two; courses can be from different areas)
Biochemistry CHEM 153A; CHEM 153B
Ecology EE BIOL 100; EE BIOL 116; EE BIOL 120; EE BIOL 129; EE BIOL 161; EE BIOL C172; EE BIOL C174
Epidemiology EPIDEM 100; MIMG 101; MIMG 102; MIMG 168; MIMG C185A
Genetics & Molecular Biology LIFESCI 107; MCD BIO 138; MCD BIO 140; MCD BIO 144; MCD BIO 165A OR 100
Neurosystems NEUROSC M101A OR PSYCH 115; NEUROSC M101B; NEUROSC 102; NEURO 205; NEURO 260; PHYSCI C144;PHYSICS C186; PSYCH 119M
Physiology BIOENGR C102; BIOMATH 206; EE BIOL 170 OR PHYSCI 166; PHYSCI 149

Additional Prep for the Major:

The following courses do not have to be completed prior to admission into the major.

Bioinformatics Track: must also complete Computer Science 32; OR Program in Computing 10B and 10C.

All Tracks: LIFESCI 23L and/or CHEM 14C/30A are recommended pre-reqs depending on chosen Life Science courses.

NOTE: Additional pre-reqs (beyond the required and recommended courses above) may be required for certain track courses. Students should check pre-reqs on the Schedule of Classes.

Track Course Planning

When planning track coursework, students must be mindful of pre-requisites. Some courses for the Bioinformatics track have additional pre-requisites that are not part of the CaSB major or pre-major curriculum. Additionally, students must be mindful of when classes are offered (i.e., which quarters).

The tables below are meant to help students plan out track coursework by providing course descriptions, requisite info, and tentative course offering info for each course option. These tables were last updated October 2021. These tables are provided as a tool, but requisites and course offerings can change. Planned course offerings, in particular, are tentative and subject to change by the departments offering each course. Students should check the Schedule of Classes or with respective departments for the most up-to-date course offerings. Students should also always check the Registrar’s Course Descriptions for the most up-to-date requisites.

It is recommended that students meet with their Departmental Counselor regularly to plan out major coursework.

Legend:

Can count as one of Bioinformatics Core track courses
Can count as one of Life Science track courses
Recommended prep course for Bioinformatics track
Pre-requisite that is not part of CaSB pre-major or major curriculum

Bioinformatics (Core)

Course Number Course Name Units Description Pre-Requisites Offering Info
COM SCI CM121 Introduction to Bioinformatics 4 (Same as Chemistry CM160A.) Lecture, four hours; discussion, two hours. Requisites: course 32 or Program in Computing 10C with grade of C- better, and one course from Civil and Environmental Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A. Prior knowledge of biology not required. Designed for engineering students as well as students from biological sciences and medical school. 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. Concurrently scheduled with course CM221. P/NP or letter grading. COM SCI 32 or PIC 10C with grade of C- or better;
One course from C&EE 110, EC ENGR 131A, MATH 170A, MATH 170E, or STATS 100A
AY 21-22: Winter 2022,
Previously taught in Fall
COM SCI CM122 Algorithms in Bioinformatics 4 (Same as Chemistry CM160B.) Lecture, four hours; discussion, two hours. Requisites: course 32 or Program in Computing 10C with grade of C- or better, and one course from Civil Engineering 110, Electrical Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A. Course CM121 is not requisite to CM122. Designed for engineering students as well as students from biological sciences and medical school. 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. Concurrently scheduled with course CM222. Letter grading. COM SCI 32 or PIC 10C with grade of C- or better;
MATH 33A;
One course from C&EE 110, EC ENGR 131A, MATH 170A, MATH 170E, or STATS 100A
Typically taught in Spring
COM SCI CM124 Machine Learning Applications in Genetics 4 (Same as Human Genetics CM124.) Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course 32 or Program in Computing 10C with grade of C- or better, Mathematics 33A, and one course from Civil Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A. Designed for engineering students as well as students from biological sciences and medical school. 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. Concurrently scheduled with course CM224. Letter grading. COM SCI 32 or PIC 10C with grade of C- or better;
One course from C&EE 110, EC ENGR 131A, MATH 170A, MATH 170E, or STATS 100A
AY 21-22: Fall 2021,
Previously taught in Winter
EE BIOL C135 Population Genetics 4 Lecture, three hours; discussion, one hour. Enforced requisite: Life Sciences 4 or 7A. Strongly recommended: course 100, Mathematics 31A, and 31B or Life Sciences 30B. Basic principles of genetics of population, dealing with genetic structure of natural populations and mechanisms of evolution. Equilibrium conditions and forces altering gene frequencies, polygenic inheritance, molecular evolution, and methods of quantitative genetics. Concurrently scheduled with course C235. Letter grading. LIFESCI 7A;
Recommended: EE BIOL 100; MATH 31A and 31B; or LIFESCI 30B
AY 21-22: Spring 2022
MCD BIO CM156 Human Genetics and Genomics 5 Same as Microbiology CM156.) Lecture, three hours; discussion, one hour. Requisites: Life Sciences 3, 4, and 23L, or 7A, 7B, and 7C. Application of genetic principles in human populations, with emphasis on genomics, family studies, positional cloning, Mendelian and common diseases, cancer genetics, animal models, cytogenetics, pharmacogenetics, population genetics, and genetic counseling. Lectures and readings in literature, with focus on current questions in fields of medical and human genetics and methodologies appropriate to answer such questions. Concurrently scheduled with course CM256. Letter grading. LIFESCI 7A, 7B, and 7C Typically taught in Winter
MCD BIO 187AL Research Immersion Laboratory in Genomic Biology 5 Lecture, three hours; laboratory, six hours. Requisites: Life Sciences 4 or 107, 23L. Course 187AL is requisite to 187BL. Limited to Molecular, Cell, and Developmental Biology majors. Introduction to cutting-edge genomic technologies and bioinformatics methods and resources for genome annotation. Students propose original research projects related to gene annotation and drive their projects using bioinformatics tools. Students are provided fragments of genome from relatively poorly studied organism that has been sequenced at UCLA. May not be repeated for credit. Letter grading. LIFESCI 107;
LIFESCI 23L
Typically taught in Spring and sometimes summer
PHYSCI 125 Molecluar Systems Biology 5 Lecture, three hours; discussion, one hour. Requisites: Life Sciences 2, 3, 4, and 23L, or 7A, 7B, 7C, and 23L. Quantitative description of molecular systems that underlie myriad phenotypes in living cells. Topics include various -omics fields and high-throughput technologies, network biology, and synthetic biology. Introductory lectures on molecular biology, emerging bioinformatic approaches, and systems modeling integrated with discussions of their applications in disease-related research. Review of recent literature to gain overall perspectives about new science of systems biology. Letter grading. LIFESCI 7A, 7B, 7C;
LIFESCI 23L
AY 21-22: Spring 2022
STATS M254 Statistical Methods in Computational Biology 4 (Same as Bioinformatics M223 and Biomathematics M271.) Lecture, three hours; discussion, one hour. Preparation: elementary probability concepts. Requisite: course 100A or 200A or Bioinformatics M221. Introduction to statistical methods developed and widely applied in several branches of computational biology, such as gene expression, sequence alignment, motif discovery, comparative genomics, and biological networks, with emphasis on understanding of basic statistical concepts and use of statistical inference to solve biological problems. Letter grading. STATS 100A or 200A or BIOINFO M221 (grad version of CS CM121) AY 21-22: Winter 2022

Other Important Information

All major courses must be taken for a letter grade, C or better.
^CaSB made a temporary exception allowing pre-major courses taken between Spring 2020 and Summer 2021 to be taken for a Pass grade. More details on this exception can be found here.

Students must have a minimum 2.0 GPA in upper-division major coursework to graduate.

Students who receive a C- or below in a major course must either repeat the course or petition to have the lower grade count for the major. More information on petitioning can be found here.

Students are subject to any requirement changes in the major, including concentrations/tracks, until they are officially admitted to the major.