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J Clin Bioinforma. 2011 Oct 3;1:26. doi: 10.1186/2043-9113-1-26.

Technical phosphoproteomic and bioinformatic tools useful in cancer research.

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Centro de Investigación i+12 del Hospital Universitario 12 de Octubre, Avda de Córdoba s/n Madrid, 28041, Spain.
Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) Campus de Cantoblanco, c/Nicolás Cabrera, 1, 28049 Madrid, Spain.
Biomol-Informatics, S.L., Parque Científico de Madrid, Campus de Cantoblanco, c/Faraday 7, 28049 Madrid, Spain.
Servicio de Hematología Hospital QUIRÓN, Madrid, Diego de Velázquez 1 28223, Pozuelo Madrid Spain.
Servicio de Digestivo, Hospital Universitario 12 Octubre, Avda de Córdoba s/n Madrid, 28041, Spain.
Contributed equally


Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools.

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