Pro-Human Extremist

Extremism in the defense of humanity is no vice

Bioinformatics laboratories

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Here is a set of Bioinformatics instructional exercises that I developed for the laboratory component of my Genomics course (BIO 294) at St Bonaventure University. The course is a requirement in our Bioinformatics major, and is an elective for Biology and Biochemistry majors.

Most of the laboratory exercises introduce students to web-based databases and computational tools used by genome biologists.  Students worked in pairs, but they could also perform them individually. Each lab started with a pre-lab discussion, followed by the doing of the lab itself, followed by a post-lab de-briefing. Each pair generated different results  and therefore had somewhat different experiences for all labs except lab 4, so the de-briefing gave students an opportunity to exchange notes and for all of us to discuss common themes.

Laboratory 1 was completed in one 3-hour laboratory period, but all of the other laboratories took more time than that. Since Spring 2011 was the first offering of these laboratories, my philosophy was to give students as much time as they needed to complete the laboratories well and without stress. As a result, some laboratory periods comprised the pre-lab discussion and the doing of the lab, with the post-lab de-briefing at the beginning of the next week’s laboratory period; or the pre-lab discussion was at the end of one week’s laboratory period, and the students started doing the lab at the beginning of the next week; etc. Laboratories 7 and 8 extended across two or more weeks. In total, the eight laboratories were completed in the fourteen weeks of the semester. The students seemed to be comfortable with this approach, and all in all these new laboratories went over remarkably well for a first offering.

Each pair of students chose a different protein to explore in labs 2, 3, and 8. As it happened,  all students chose proteins produced by humans, which was nice because human genes are especially well-annotated, but this isn’t necessary.

Preparatory readings come from Jonathan Pevsner’s Bioinformatics and Functional Genomics, which is the best genomics/bioinformatics textbook I’ve seen.

These laboratories are copyright 2011, Joel Benington. They are provided here as a service to the genomics community. Please contact me before adapting them for use in your own course.

Laboratory 1—Using the NCBI genome viewer

An introduction to the NCBI genome viewer interface, giving students an opportunity to explore the genome landscape in a prokaryote. Each pair of students catalogs properties of genes in a different 20kb segment of the genome.

Instructions                  Report

Laboratory 2—Exploring the NCBI Entrez Gene database

An open-ended exploration of the NCBI Entrez Gene database. Each pair of students explores the entry for a different gene.

Instructions                  Report

Laboratory 3— Exploring the Ensembl database

An open-ended exploration of the Ensembl database. Each pair of students explores the entry for a different gene.

Instructions                  Report

Laboratory 4—DNA sequence assembly

A simulation of genome assembly of a part of the HIV genome. This laboratory is adapted from one written by Robert M. Horton, Ph.D., and included in the Cybertory Project.

Instructions                  Report

Laboratory 5—Gene prediction and BLAST

The GeneMark gene-prediction algorithm is used to predict genes in segments of the Drosophila melanogaster genome. BLAST is then used to identify the actual gene annotations, for comparison with the predicted annotations.

Instructions                  Report

Laboratory 6—DNA sequence alignment

The Needleman and Wunsch algorithm is used to align short amino acid sequences, and then NCBI’s BLAST interface is used to perform pairwise alignments of longer amino acid sequences.

Instructions                  Report

Laboratory 7—Constructing phylogenetic trees based on genetic distance

Parsimony and UPGMA distance methods are used to construct phylogenetic trees based on polypeptide sequences, and then the Cobalt tool at NCBI is used to perform multiple sequence alignments and construct phylogenetic trees based on them.

Instructions                  Report

Laboratory 8—Protein structure

An exploration of databases and software for visualizing protein structures, and relating protein structural information to what is known about the functioning of proteins.

Instructions                  Report

Written by Joel Benington

June 20, 2011 at 6:04 pm

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