Identifying Unknown Bacteria Using Biochemical and Molecular Methods
Students use two different protocols, one based on sequence analysis and one based on biochemistry, to determine the identity of an unknown bacterial strain.
Students use two different protocols, one based on sequence analysis and one based on biochemistry, to determine the identity of an unknown bacterial strain.
This lab provides an opportunity for students to randomly clone a fragment of the yeast genome into E. coli and then investigate what part of the genome they have cloned through sequence analysis.
This PowerPoint presentation provides a brief introduction to the different types of RNA-Seq evidence tracks (e.g. Bowtie, TopHat, Cufflinks) that are on the GEP UCSC Genome Browser.
Developed by Dr. Ken Saville (Albion College) and Dr. Gerard McNeil (York College, City University of New York), this walkthrough provides a comprehensive overview of the entire GEP gene annotation process. This walkthrough includes a brief description of the research problem and step-by-step instructions on how to use the UCSC Genome Browser, FlyBase, the Gene Record Finder and NCBI BLAST to investigate a feature in a Drosophila erecta Muller F element annotation project. The walkthrough then shows how students can use the Gene Model Checker to verify a gene model; it also includes a sample GEP Annotation Report.
Ms. Julie Ertmann (University City High School, MO) has designed a standalone activity using BLAST for AP or second year high school biology students. This exercise uses BLAST and ExPASy for genetic and protein analysis of H1N1 variability, including mutations that confer resistance to antiviral medications. Development of this exercise was supported by an NSF Mathematics and Science Partnership grant #06344780, to B Schaal, Washington University in St. Louis. If you have questions about this activity, please email the author at: jertmann@ucityschools.org.
Students use the HIV Problem Space on the BioQuest BEDROCK Website to investigate whether a specific HIV mutation can be correlated with a decline in immune system function. In order to perform this analysis, students must generate and analyze multiple sequence alignments of HIV sequences generated from the ALIVE study.