Professor Hirsch teaches AGRO5431: Applied Plant Genomics and Bioinformatics during Spring semesters. This is a 3 credit class open to undergraduate and graduate students.
Course Overview
With advances in technology and software over the last decade it is now possible to access the complete genome, transcriptome, and epigenome of multiple accessions within a species. Large-scale genomics datasets have been used to answer basic biological questions as well as provide unprecedented tools for the applied sciences. The accessibility and utility of large-scale genomics datasets for model and non-model species is only increasing. This course provides students with skills necessary to analyze, interpret, and visualize large plant genomic datasets. Students who complete this course are capable of basic computer programming, applying large-scale genomics to answer basic and applied biological questions, understanding the limitations of each application, and presenting concise visual findings from large-scale datasets. This course involves lectures and computer lab activities in which students utilize publicly available bioinformatics resources via the web and at the Minnesota Supercomputing Institute (MSI) to analyze genomic data.
Student Learning Outcomes
Students in Applied Plant Genomics and Bioinformatics will learn:
- Basic computer programming in Unix, R, and Python
- To work in a high throughput computing infrastructure (i.e. MSI)
- Principles of genomics experimental design and quality control analysis of genomics datasets
- How to detect sequence variants
- Genome and transcriptome assembly
- How to analyze and interpret transcriptome data
- How to visualize large-scale genomics datasets
- How to apply these concepts to answer basic and applied biological questions
For questions about the course, please email [email protected].