Computational analyses of large-scale datasets have become central to modern biology. In this class, students will learn how 'omics' techniques such as genomics, transcriptomics, and proteomics can help to answer questions in diverse fields ranging from cell biology to ecology and evolution. Lectures and discussions of primary literature will utilize examples from microbiology to introduce students to the design, analysis, and interpretation of 'omics'-based studies. We will explore the theory behind key bioinformatic algorithms and gain hands-on experience applying these tools to real datasets. The laboratory will culminate in an original research project utilizing genomic data to study microbial ecosystems. Topics covered include genome sequencing, assembly and interpretation; comparative genomics; metagenomics; transcriptomics; metabolic models; network analysis; and machine learning.

This course has a required co-requisite Laboratory - BISC 333L.

Units: 1.25

Max Enrollment: 14

Prerequisites: BISC 219/BIOC 219 or BISC 209; or permission of the instructor.

Distribution Requirements: LAB - Natural and Physical Sciences Laboratory; NPS - Natural and Physical Sciences

Typical Periods Offered: Spring

Semesters Offered this Academic Year: Spring

Notes: Ann E. Maurer '51 Speaking Intensive Course.