• FlyBase: Enhancing Drosophila Gene Ontology annotations

      Tweedie, S; Ashburner, M; Falls, K; Leyland, P; McQuilton, P; Marygold, S; Millburn, G; Osumi-Sutherland, D; Schroeder, A; Seal, R; Zhang, H; Gelbart, W; Bitsoi, L; Crosby, M; Dirkmaat, A; Emmert, D; Gramates, LS; Falls, K; Kulathinal, R; Matthews, B; Roark, M; Russo, S; Schroeder, A; St Pierre, S; Zhang, H; Zhou, P; Zytkovicz, M; Brown, N; Leyland, P; Stefancsik, R; Tweedie, S; Williams, M; Kaufman, T; Matthews, K; Goodman, J; Grumbling, G; Strelets, V; Wilson, R; Kulathinal, Rob|0000-0003-1907-2744 (2009-01-09)
      FlyBase (http://flybase.org) is a database of Drosophila genetic and genomic information. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. This article describes recent changes to the FlyBase GO annotation strategy that are improving the quality of the GO annotation data. Many of these changes stem from our participation in the GO Reference Genome Annotation Project - a multi-database collaboration producing comprehensive GO annotation sets for 12 diverse species. © 2008 The Author(s).
    • The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation

      Loevenich, SN; Brunner, E; King, NL; Deutsch, EW; Stein, SE; Aebersold, R; Hafen, E; Gelbart, W; Bitsoi, L; Crosby, M; Dirkmaat, A; Emmert, D; Gramates, LS; Falls, K; Kulathinal, R; Matthews, B; Roark, M; Russo, S; Schroeder, A; St. Pierre, S; Wiley, K; Zhang, H; Zhou, P; Zytkovicz, M; Brown, N; Leyland, P; McQuilton, P; Marygold, S; Millburn, G; Osumi-Sutherland, D; Stefancsik, R; Tweedie, S; Kaufman, T; Matthews, K; Goodman, J; Grumbling, G; Strelets, V; Wilson, R; Kulathinal, Rob|0000-0003-1907-2744 (2009-02-11)
      Background: Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments. Results: In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal http://www.drosophila-peptideatlas.org allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed. Conclusion: PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert. © 2009 Loevenich et al; licensee BioMed Central Ltd.