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.
Adding a proteome to GPM Personal Editions
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.
Sanibel conference, 2011.01.23 12:00 EST
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.
Discussion: Knowledgebases in PTM Analysis
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.
Case: Finding phosphorylation sites using GPMDB and pSYT
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.
Discussion: Interpreting details found in high-throughput data
Santa and Hillary discuss the difficulties of assigning specific 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