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BIOENGC249

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BIOENG C249 - Computational Functional Genomics

Bioengineering Graduate COE - College of Engineering

Subject

BIOENG

Course Number

C249

Course Level

Graduate

Course Title

Computational Functional Genomics

Course Description

This course provides a survey of the computational analysis of genomic data, introducing the material through lectures on biological concepts and computational methods, presentations of primary literature, and practical bioinformatics exercises. The emphasis is on measuring the output of the genome and its regulation. Topics include modern computational and statistical methods for analyzing data from genomics experiments: high-throughput RNA sequencing data, single-cell data, and other genome-scale measurements of biological processes. Students will perform original analyses with Python and command-line tools.

Minimum Units

4

Maximum Units

4

Grading Basis

Default Letter Grade; S/U Option

Instructors

Lareau

American Cultures Requirement

No

Reading and Composition Requirement

None of the Reading and Composition Requirement

Prerequisites

Math 54 or EECS 16A/B; CS 61A or another course in python; BioE 11 or Bio 1a; and BioE 131. Introductory statistics or data science is recommended

Repeat Rules

Course is not repeatable for credit.

Credit Restriction Courses

-

Credit Replacement Courses

-

Course Objectives

This course aims to equip students with practical proficiency in bioinformatics analysis of genomic data, as well as understanding of the biological, statistical, and computational underpinnings of this field.

Student Learning Outcomes

Students completing this course should have stronger programming skills, practical proficiency with essential bioinformatics methods that are applicable to genomics research, understanding of the statistics underlying these methods, and awareness of key aspects of genome function and challenges in the field of genomics.

Cross-Listed Course(s)

Formats

Lecture, Discussion

Term

Fall and Spring

Weeks

15 weeks

Weeks

15

Lecture Hours

3

Lecture Mode of Instruction

In Person

Discussion Hours

1

Discussion Mode of Instruction

In Person

Outside Work Hours

8