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Applied Bioinformatics: Microbiomes
Last Updated: 2026-02-05 15:47:07
Abstract
Learn to apply practical bioinformatics/computational skills for analysis of microbiomes in foods and human health! Students will apply basic programming skills for scientific computing and bioinformatics, and learn and discuss the importance of microbiomes to foods and human health, through recognition and comparison of ecological theory, methodology, and experimental design across systems.
Objective
Learn to apply bioinformatics and computational methods for analysis of microbiome next-generation sequencing data. A secondary goal is to critically examine the relevance of microbiomes to food quality, safety, and human health, through application of theory and appropriate experimental design. Students completing this course will thus be able to both apply appropriate methodology to study microbiomes (or other high-dimensional data) in different systems, as well as evaluate and interpret bioinformatics results.
Content
1. Introduction to microbiomes and microbial bioinformatics toolkit. UNIX/bash, Python, Pandas, Jupyter, git/GitHub, visualization libraries for Python. 2. Analysis of marker-gene sequence data for microbiome profiling. QIIME 2, database searching, taxonomic classification, phylogenetics. 3. Microbial diversity, function, and ecology. Molecular ecology, diversity metrics, ordination methods. 4. Advanced topics in microbial bioinformatics. Metagenomics, machine learning, functional analysis, data visualization, et cetera. This course requires extensive engagement in learning outside of the classroom (using online resources and practical exercises), with a focus on active learning in the classroom.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 20
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Applied Bioinformatics: Microbiomes |
|
2 h weekly |