What higher-level computational skills can be used in bioinformatics research?
- Use a spreadsheet to perform simple data analysis.
- Use a spreadsheet to open, read, parse, modify and output comma-separate (.csv) files that will be ready to use in subsequent tools.
- Perform elementary statistical analysis on an “omics” dataset (e.g. using Excel or Weka).
- Perform Input/Output with data files.
- Interact with remote servers.
- Construct a bioinformatics pipeline.
- Use open source libraries and packages (e.g., BioPerl, Biopython, R, BioConductor).
- Use programs at the Unix/Linux command line to analyze bioinformatics data.
- Use graph theory to represent data networks.
- An Introduction to Eukaryotic Genome Analysis in Non-model Species for Undergraduates: A tutorial from the Genome Consortium for Active Teaching
- Investigating Cell Signaling with Gene Expression Datasets
- Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching