There are many Undergraduate course offerings in Bioinformatics at UCLA.
Course Choices: Intro Courses vs. Bioinformatics Core sequence
For biology students interested in an introduction to genomics and bioinformatics tools, there are several courses available that do not require programming or statistics prerequisites: Chemistry C100 “Genomics and Computational Biology”, MCDB 172 “Genomics and Systems Biology”, EEB 135 “Population Genetics”, Human Genetics 144 “Genomic Technology”, and PhySci 125 “Molecular Systems Biology”.
Students who want an in-depth introduction to bioinformatics theory and methods should take the bioinformatics core course sequence: Computer Science 121 (also Chem 160A) “Introduction to Bioinformatics”, Computer Science 122 (also Chem 160B) “Advanced Algorithms in Bioinformatics and Systems BIology”, and Computer Science 124 (also Human Genetics 124) “Computational Genetics”. They require statistics and programming prerequisites:
- Statistics 100A or Math 170A or Biostatistics 100A or 110A
- AND one of Program In Computing (PIC) 10C or Computer Science 32.
In order to take PIC 10C or Computer Science 32, students should complete PIC 10A,10B or Computer Science 31. Mathematics 33A is also strongly recommended for students interested in taking the core courses. The Life Science 1,2,3,4 series is recommended for students interested in Bioinformatics.
Core Course Descriptions:
Computer Science 121. Introduction to Bioinformatics and Genomics. (4)
(Same as Chemistry CM160A.) Lecture, four hours; discussion, two hours. Recommended requisites: CS32 or Program in Computing 10C, and Biostatistics 100Aor 110A or Mathematics 170A or Statistics 100A. Introductionto bioinformatics and methodologies, with emphasis on concepts andinventing new computational and statistical techniques to analyzebiological data. Focus on sequence analysis and alignment algorithms.The course is intended for both students in engineering as well asstudents from the biological sciences and medical school. No priorknowledge of biology is required. Concurrently scheduled with course Computer Science CM221. P/NP or letter grading.
Computer Science 122. Algorithms in Bioinformatics and Systems. (4)
(Same as Chemistry CM160B) . Lecture, four hours; discussion, two hours. Recommended requisite: Computer Science 32 or Program in Computing 10C, and and Biostatistics 100A or 110A or Mathematics 170A or Statistics 100A. Development andapplication of computational approaches to biological questions. Focuson formulating interdisciplinary problems as computational problemsand then solving these problems using algorithmic techniques. Thecomputational techniques discussed include techniques from statisticsand computer science. The course is intended for both students inengineering as well as students from the biological sciences andmedical school. Concurrently scheduled with course Computer Science CM222. Letter grading.
Computer Science 124. Computational Genetics (4)
(Same as Human Genetics CM124.) Lecture, four hours; discussion, two hours. Recommended requisite: Computer Science 32 or Program in Computing 10C, and and Biostatistics 100A or 110A or Mathematics 170A or Statistics 100A. 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 geneticsequencing. Focus on formulating interdisciplinary problems as computational problems and then solving these problems using computational techniques. The computationaltechniques discussed include techniques from statistics and computer science. The course is intended for both students in engineering as well as students from the biological sciences and medical school. Concurrently scheduled with course Computer Science CM224. Letter grading.
Other Available Bioinformatics Course Descritions:
Chemistry C100. Genomics and Computational Biology. (5)
Lecture, three hours; discussion, one hour. Requisite: course 153B. Introduction for biochemistry students of technologies and experimental data of genomics, as well as computational tools for analyzing them. Biochemistry and molecular biology dissected life into its component parts, one gene at time, but lacked integrative mechanisms for putting this information back together to predict what happens in complete organism (e.g., over 80 percent of drug candidates fail in clinical trials). High-throughput technologies such as sequencing, microarrays, mass-spec, and robotics have given biologists incredible new capabilities to analyze complete genomes, expression patterns, functions, and interactions across whole organisms, populations, and species. Use and analysis of such datasets becomes essential daily activity for biomedical scientists. Core principles and methodologies for analyzing genomics data to answer biological and medical questions, with focus on concepts that guide data analysis rather than algorithm details. Concurrently scheduled with course C200. P/NP or letter grading
Molecular, Cell and Developmental Biology 172. Genomics and Bioinformatics. (5)
Lecture, three hours; discussion, one hour. Requisite: course 144 or 165B or Chemistry 153B or Microbiology 132. Genomics is study of complete repertoire of molecules in cells. Topics include human and yeast genomes and genetic approaches to study of function of individual genes, fundamental bioinformatics algorithms used to study relationship between nucleotide and protein sequences and reconstruction of their evolution, use of microarray technologies to measure changes in gene expression, analysis of microarray data including clustering and promoter analysis, proteomics topics including protein expression and interactions, epigenomic study of DNA methylation and chromatin modification, and systems biology, or computational approaches to integrating varied genomic data to gain more complete understanding of cellular biology. Letter grading.
Physiological Sciences 125. Molecular Systems Biology. (4)
Lecture, three hours; discussion, one hour. Enforced requisites: Life Sciences 1, 2, 3, 4. 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.
Ecology and Evolutionary Biology C135. Population Genetics. (4)
Lecture, three hours; discussion, one hour. Requisite: Life Sciences 4. Strongly recommended: course 100, Mathematics 31A, 31B. 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.
Human Genetics C144. Genomic Technology. (4)
Lecture, three hours; discussion, one hour. Requisite: Life Sciences 4. Survey of key technologies that have led to successful application of genomics to biology, with focus on theory behind specific genome-wide technologies and their current applications. Concurrently scheduled with course C244. S/U or letter grading.