Graphical Abstract
Sample extraction, separation and data acquisition/processing are sequentially executed to get protein expression profiles from a given sample. To retrieve all the information embedded in the result files, it is important to translate raw files into accepted standards (MIAPE (Minimum Information About a Proteomics Experiment) guidelines and HUPO-PSI xml formats). Data standardization enables to normalize the data obtained from distinct experimental platforms. Remarkably, it provides a way to reanalyse datasets post-publication using public repositories such as ProteomeXchange (PX). Thanks to these repositories, scientists are able to download and reanalyse the data using specific search-criteria or with up-to-date databases, to refine or complement their studies.
Finally, proteomics results can be linked to functional and biological databases to integrate gathered information in a systems biology network. Several resources regarding metabolic pathways (KEGG, Biocarta), their reported molecular interactions (IntAct, STRING), their possible role in diseases (OMIM), as well as their posttranslational modifications (Phosphosite, Phosida), biological functions or molecular process (Gene Ontology, GO) can all be compiled through curated and freely available repositories.
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Medina-Aunon, J.A., Albar, J.P. (2014). Standards for Proteomics Data Dissemination and Experiments Reporting. In: Marko-Varga, G. (eds) Genomics and Proteomics for Clinical Discovery and Development. Translational Bioinformatics, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9202-8_4
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