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. 2012 Jul 25;139(9):1103–1118. doi: 10.1017/S0031182012000716

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Copyright © Cambridge University Press 2012. The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence <http://creativecommons.org/licenses/by-nc-sa/2.5/>. The written permission of Cambridge University Press must be obtained for commercial re-use.

The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence <http://creativecommons.org/licenses/by-nc-sa/2.5/>. The written permission of Cambridge University Press must be obtained for commercial re-use.

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Fig. 2 — A bioinformatics pipeline for large-scale proteomics data storage, querying and interpretation. The involvement of various bioinformatics tasks in processing and interpreting proteomics data is summarised. Raw mass spectra data collected from an experimental pipeline are subjected to proteomics identification packages, where protein identifications are acquired based on the comparison between raw data and protein sequence databases. The results are then analysed by appropriate quantification packages where relative or absolute quantifications of the analyte proteins are calculated. Protein function and localization prediction and pathway analysis tools have been developed to infer the biological meaning of the identification and quantification data. Proteogenomic and database integration pipelines are available to facilitate data integration with online databases and improve genome annotation using alternate annotations.