The GPMDB contains thousands of data sets contributed by researchers around the world. The large volume of data and biological complexity means that it can be a little intimidating for first time users to figure out how to extract information form the database. This page contains our video tutorials for using the system, presented as a set of case studies and discussions.

This video describes the steps required to add a new proteome/FASTA sequence file to GPM-PE so that it can be used from the GPM Manager application. The same steps apply to any install of GPM.

This video is a dramatization of a talk given by Ron Beavis at the ASMS Sanibel conference in 2011, held in St. Petersberg, FL. The talk explains some of the objective measures that we use at GPM to try to understand the quality of data sets for use in annotated spectrum library creation. These same measures can be used to check search engine results, particular when changes are made to the underlying algorithms. A PDF version of the slides for this talk can be downloaded here.

This video discusses the mechanism that X! Tandem and P3 use to change the potential modifications tested on a protein-by-protein basis. The video refers to the following references:

• Biemann, K. and Martin, S. A. (1987) Mass spectrometric determination of the amino acid sequence of peptides and proteins. Mass Spectrom. Rev., 6, 1-76.
• Boeckmann, B., et al. (2005) Protein variety and functional diversity: Swiss-Prot annotation in its biological context. Compt. Rend. Bio., 328, 882-899.
• Craig R., et al. (2006) Using annotated peptide mass spectrum libraries for protein identification. J Proteome Res, 5, 1843-1849.
• Craig, R. and Beavis, R.C. (2004) TANDEM: matching proteins with mass spectra, Bioinformatics, 20, 1466-7.
• Eng, J., et al. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom., 5, 976-989.
• Fenyö, D. (1999) The Biopolymer Markup Language, Bioinformatics, 15, 339-40.
• Lederberg, J., et al. (1969) Applications of artificial intelligence for chemical inference. I. The number of possible organic compounds. Acyclic structures contain-ing C, H, O, and N. J. Am. Chem. Soc., 91, 2973-2976.
• Slebos, R.J.C. et al. (2008) Evaluation of Strong Cation Exchange versus Isoelectric Focusing of Peptides for Multidimensional Liquid Chromatography-Tandem Mass Spectrometry. J. Proteome Res., 7:5286-5294.
• Smedley, D. et al. (2009) BioMart - biological queries made easy. BMC Genomics, 10:22.
• Tabb, D.L., et al. (2007) MyriMatch: Highly Accurate Tandem Mass Spectral Peptide Identification by Multivariate Hypergeometric Analysis. J. Proteome Res., 6:654-661.

This video describes the steps necessary to find the observed phosphorylation sites for a particular protein. The description is in the form of a dialogue between a biomedical researcher (as played by HRM Queen Elizabeth II) and a GPMDB power user (Beavo the clown). Together, they get the researcher started obtaining the phosphorylation sites for her protein of interest C21orf66 and its corresponding pSYT entry.

Two characters discuss the issues associated with discovering post-translational modifications and alternately spliced protein sequences from high throughput data and give some advice. The script was adapted from our list of suggested interpretation guidelines.