Applications will open soon. To be notified, please contact the Education Office.
The goal of the Applied Bioinformatics Course is to provide hands-on training on major bioinformatics resources through the analysis of an RNA-Seq data set to find differentially expressed genes and investigate previously described functions of those genes and the pathways they are involved in.
Topics include web-based gene and protein resources, genome browsers, pathways and gene set enrichment analyses, and RNA-Seq data analysis. RNA-Seq data analysis will be conducted using CLC Genomics Workbench, the web-based Galaxy system, R statistical computing environment and Ingenuity Pathways Analysis. The course will feature several modules that will have written worked examples to demonstrate how to apply the major tools or resources featured in the module. Participants should have a strong background in molecular biology. Prior computer programming skills are not required, but participants need to have a strong interest in learning some programming concepts.
- Britton Goodale, Ph.D.Postdoctoral FellowGeisel School of Medicine, Dartmouth College
- Casey S. Greene, Ph.D.Assistant ProfessorUniversity of Pennsylvania
- Thomas H. Hampton, M.S.Senior Bioinformatics AnalystGeisel School of Medicine at Dartmouth
- Katja Koeppen, Ph.D.Research ScientistGeisel School of Medicine, Dartmouth College
- W. Kelley Thomas, Ph.D.Director, Hubbard Center for Genome StudiesUniversity of New Hampshire