Course content varies by section and is selected to fill timely and special interests and needs of students. See CS 7501 for example topics. May be repeated for credit when topic varies. Prerequisite: Instructor permission.

Graduate-level independent study conducted under the supervision of a specific instructor(s)

The class covers statistical and programming background as well as introduction to software tools for analysis of functional genomics data sets and will focus on analysis of high throughput sequence data including RNA-Seq and ChIP-Seq. Students will also learn how to further summarize their data from a regulatory network perspective by performing TF-DNA motif, metabolic/signaling pathway and gene ontology (GO) analysis. Prerequisite: Bioinformatics and Protein Structure or permission of instructor

Students will learn foundational computational methods for analysis of data from genome, epigenome, and transcriptome sequencing experiments. The course will cover various biological data types, algorithms, statistical and computational methods, and application areas in genomics and systems biology. Prior coursework/experience in linear algebra, UNIX, and R and Python programming required.

This course is for visiting research students participating in the BIMS Visiting Research Graduate Trianeeship Program (VRGTP). Students in this course are dual enrolled in their home institution and will participate in research for a minimum of 4 semesters. The research will assist them in completing their degree at their home institution. Non-degree students.

Topical Research

Non-Topical Research: Preparation for Doctoral Research

For doctoral dissertation, taken under the supervision of a dissertation director.

For doctoral research, taken under the supervision of a dissertation director.