ECOS1200 Advanced bioinformatics: microbial communities and genomes (5 cr)
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Description
The course teaches the students to use bioinformatics methods to analyse genetic and genomics data, so that they can understand processes affecting community composition and genome diversity.
The course focuses on the use of next generation sequence data to analyse microbial communities and microbial genomes, although the capability to retrieve and analyse data using remote computing and analyse data using bioinformatics software are taught as skills that can be readily transferred to other bioinformatic analyses.
After providing guidance about sequencing technologies and an introduction to using UNIX, the course then instructs students how to inspect data quality, clean data and complete community analyses. The second part of the course examines methods of genome assembly and annotation.
The course is implemented using a series of lectures and computer-based practical exercises (supported by self-instructional handouts so that students can work at their own pace).
Students are expected to complete independent work and also work within a group to complete interpretation tasks.
Learning outcomes
After completing the course, the student will
· be able to search and retrieve data from open sources,
· understand principles behind different types of next generation sequencing technology,
· be capable of using UNIX command line to analyse data using remote computing facilities,
· be able to use diverse bioinformatics tools to complete tasks (e.g. clean data, analyse community data, assemble genome),
· be capable of producing reproducible analyses, and
· be able to interpret his/her research critically and report back to others.
Additional information
The course aims to complement CMBS2404 by extending the analyses of data collected in that course.
The course is offered every other year: spring 2025, 2027
Description of prerequisites
Recommended: BENA2008 Introduction to bioinformatics, BENA2005 Evolutionary Biology or equivalent. Familiarity with R is useful but not required.
Study materials
Principal study materials are recent scientific articles and course handouts.