Graduate Programs

Graduate Programs

UCSF has several different graduate programs with courses that cover topics in genetics. Below are the different courses listed per graduate program, with a link to the program itself that can provide more info on their scientific focus.

Biomedical Sciences (BMS)

BMS is an interdisciplinary graduate research program that seeks to equip students with the training and research tools to study the function of tissue and organ systems in development, physiology, and disease.

BMS Website

BMS255, Genetics

Course Directors: Christian Vaisse, PhD & Anita Sil, PhD |

Scope of the graduate level course in Genetics is to convey an understanding of basic genomics and molecular genetics, use of genetic animal model systems and of the analytical principles of simple and complex human genetic traits.

Pharmaceutical Sciences & Pharmacogenomics (PSPG)

PSPG is a multidisciplinary graduate program has a dual focus: pharmaceutical sciences and drug development, and pharmacogenomics, which is the application of genetics and genomics to drug action and disposition. The result of this dual focus is that it trains the next generation of scientists to explore new drugs in novel ways.

PSPG Website

PSPG245C, Principles of Pharmacogenomics

Course Director: Nadav Ahituv, PhD |

To understand genetic factors underlying efficacy/toxicity of drug therapy; to assess the value of phenotyping/genotyping in guiding drug therapy of individual patients; to evaluate genomic methods in drug design, development, and therapy.

Biochemistry & Molecular Biology, Cell Biology, Developmental Biology & Genetics (Tetrad)

The Tetrad graduate program offers diverse training and opportunities in four major research areas: biochemistry and molecular biology, cell biology, developmental biology, and genetics. The program is interdisciplinary, with an emphasis on collaborations among laboratories to solve outstanding problems in modern biology.

Tetrad Website

Genetics 200A, Principles in Molecular Genetics

Course Director: David Toczyski, PhD |

An in-depth analysis of genetic mechanisms in selected prokaryotes and eukaryotes. Topics include recombination, mutagenesis, gene expression, meiotic and mitotic segregation, and developmental genetics.

Biological and Medical Informatics (BMI)

The BMI program readies scientists to master and interpret, through the use of sophisticated tools and computational models, the rapidly growing amount of information about human biology.

BMI Website

BMI206, Statistical Methods

Course Director: Katie Pollard, PhD |

This course covers a survey of bioinformatics research areas and statistical methods needed to analyze data in these areas. The overall goal is to empower students to select and implement appropriate statistical analyses in research problems with large and complex data structures. Bioinformatics topics include: functional genomics (RNA-seq, ChIP-seq), genetic variation (eQTLs, GWAS), biological networks. Statistical methods include: linear (LMs) and generalized linear models (GLMs), multiple-hypothesis testing, model selection, network statistics, Bayesian inference, multivariate distributions, clustering.

Epidemiology & Translational Sciences (ETS)

The Doctoral Program in ETS includes courses in bioinformatics, biostatistics, and epidemiology. The PhD program in Epidemiology and Translational Science, a collaboration between the Department of Epidemiology and Biostatistics and UCSF’s renowned Clinical and Translational Sciences Institute, offers high caliber training in core skills of epidemiologic and biostatistical methods along with practical research rotations that enhance classroom training.

ETS Website

EPI 217, Molecular and Genetic Epidemiology

Course Directors: John Witte, PhD and Thomas Hoffmann, PhD |

Genetic epidemiology is one area of concentration within the ETS program. The course in Molecular and Genetic Epidemiology introduces the concepts, principles, and use of molecular and genetic methods in epidemiologic and clinical research and how to develop a framework for interpreting, assessing, and incorporating molecular and genetic measures in research.