Literature DB >> 23482073

The HUPO proteomics standards initiative- mass spectrometry controlled vocabulary.

Gerhard Mayer1, Luisa Montecchi-Palazzi, David Ovelleiro, Andrew R Jones, Pierre-Alain Binz, Eric W Deutsch, Matthew Chambers, Marius Kallhardt, Fredrik Levander, James Shofstahl, Sandra Orchard, Juan Antonio Vizcaíno, Henning Hermjakob, Christian Stephan, Helmut E Meyer, Martin Eisenacher.   

Abstract

Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)-Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS-related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies. Database URL: http://psidev.cvs.sourceforge.net/viewvc/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo.

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Year:  2013        PMID: 23482073      PMCID: PMC3594986          DOI: 10.1093/database/bat009

Source DB:  PubMed          Journal:  Database (Oxford)        ISSN: 1758-0463            Impact factor:   3.451


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