Abstract
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.
Current Topics in Medicinal Chemistry
Title:Bioinformatics Tools for the Functional Interpretation of Quantitative Proteomics Results
Volume: 14 Issue: 3
Author(s): Teresa Nunez Villavicencio-Diaz, Arielis Rodriguez-Ulloa, Osmany Guirola-Cruz and Yasset Perez-Riverol
Affiliation:
Keywords: Bioinformatics, biological network analysis, candidate gene prioritization, comparative proteomics, data interpretation, enrichment analysis, text mining.
Abstract: 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.
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Cite this article as:
Villavicencio-Diaz Nunez Teresa, Rodriguez-Ulloa Arielis, Guirola-Cruz Osmany and Perez-Riverol Yasset, Bioinformatics Tools for the Functional Interpretation of Quantitative Proteomics Results, Current Topics in Medicinal Chemistry 2014; 14 (3) . https://dx.doi.org/10.2174/1568026613666131204105110
DOI https://dx.doi.org/10.2174/1568026613666131204105110 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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