Proteins are the principal mediators of the functions in the cell; therefore, any abnormal variations on their
abundance levels may reflect the presence of pathological processes. In this sense, many researchers rely on the functional
interpretation of protein lists generated by quantitative proteomics experiments to analyze, for instance, these variations in
the context of diseases´ molecular basis and drug discovery. Since no analytical strategy or bioinformatics tool by itself is
capable of extract all the information covered by a single experiment; herein we seek to provide the biologists with four
groups of different but complementary bioinformatics tools for the functional interpretation of quantitative proteomics results.
To this end we will review the basic concepts of a set of different bioinformatics approaches and we will give examples
of freely available tools for each one of these approaches.
Keywords: Bioinformatics, biological network analysis, candidate gene prioritization, comparative proteomics, data interpretation,
enrichment analysis, text mining.
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