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CMPBIOC149

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CMPBIO C149 - Computational Functional Genomics

Computational Biology Graduate Group Undergraduate CDSS - Clg of Comp Data Sci & Society

Subject

CMPBIO

Course Number

C149

Department

Computational Biology Graduate Group

Course Level

Undergraduate

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; P/NP Option

Method of Assessment

Alternative Final Assessment

Instructors

Lareau

Prerequisites

MATH 54 or ELENG 64/ELENG 66; COMPSCI 61A or equivalent Python course; BIOENG 11 or BIOLOGY 1A; and BIOENG 131. Introductory statistics or data science is recommended.

Repeat Rules

Course is not repeatable for credit.

Credit Restriction Courses. Students will receive no credit for this course if following the course(s) have already been completed.

-

Credit Replacement Courses. Upon passing, students can use the following course(s) to replace a deficient grade for this course.

-

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 Hours Min

3

Lecture Hours Max

3

Lecture Mode of Instruction

In Person

Discussion Hours

1

Discussion Hours Min

1

Discussion Hours Max

1

Discussion Mode of Instruction

In Person

Outside Work Hours

8

Outside Work Hours Min

8

Outside Work Hours Max

8