Computational Molecular Biology Option
This option is offered within the following major(s):
The Computational Molecular Biology option is designed for students interested in the interface of molecular biology, computer science, and statistics. It provides strong preparation for graduate school in computational biology as well as the biotechnology and pharmaceutical industry workforce. This option couples the comprehensive core training in biochemistry and molecular biology with advanced course work in mathematics, statistics, computer science, and bioinformatics. Students are strongly encouraged to participate in undergraduate research, and up to six research credits can be applied to the Upper-division Science Elective requirements. Faculty advisors work with students to identify elective courses, undergraduate research opportunities, and professional internships that support their individual interests.
Option Code: 973
| Code | Title | Credits |
|---|---|---|
| Core | ||
| BB 485 | APPLIED BIOINFORMATICS | 3 |
| CS 161 | INTRODUCTION TO COMPUTER SCIENCE I | 4 |
| Electives | ||
| Select 14 or more credits of the following: | 14 | |
| UNDERGRADUATE RESEARCH | ||
| GENETICS | ||
| FUNCTIONAL GENOMICS | ||
| COMPARATIVE GENOMICS | ||
BOT 476 | ||
| INTRODUCTION TO COMPUTER SCIENCE II | ||
| DATA STRUCTURES | ||
| ANALYSIS OF ALGORITHMS | ||
| GRAPH THEORY WITH APPLICATIONS TO COMPUTER SCIENCE | ||
| NETWORKS IN COMPUTATIONAL BIOLOGY | ||
| MICROBIAL GENOMES, BIOGEOCHEMISTRY, AND DIVERSITY | ||
| ELEMENTS OF DISCRETE MATHEMATICS | ||
| INTRODUCTION TO STATISTICAL METHODS | ||
or ST 411 | METHODS OF DATA ANALYSIS | |
or ST 412 | METHODS OF DATA ANALYSIS | |
| Total Credits | 21 | |
Option Code: 973