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Approaches for targeted proteomics and its potential applications in neuroscience.
J Biosci ; 2015 Sept; 40(3): 607-627
Article em En | IMSEAR | ID: sea-181440
An extensive guide on practicable and significant quantitative proteomic approaches in neuroscience research is important not only because of the existing overwhelming limitations but also for gaining valuable understanding into brain function and deciphering proteomics from the workbench to the bedside. Early methodologies to understand the functioning of biological systems are now improving with high-throughput technologies, which allow analysis of various samples concurrently, or of thousand of analytes in a particular sample. Quantitative proteomic approaches include both gel-based and non-gel-based methods that can be further divided into different labelling approaches. This review will emphasize the role of existing technologies, their advantages and disadvantages, as well as their applications in neuroscience. This review will also discuss advanced approaches for targeted proteomics using isotope-coded affinity tag (ICAT) coupled with laser capture microdissection (LCM) followed by liquid chromatography tandem mass spectrometric (LC-MS/MS) analysis. This technology can further be extended to single cell proteomics in other areas of biological sciences and can be combined with other ‘omics’ approaches to reveal the mechanism of a cellular alterations. This approach may lead to further investigation in basic biology, disease analysis and surveillance, as well as drug discovery. Although numerous challenges still exist, we are confident that this approach will increase the understanding of pathological mechanisms involved in neuroendocrinology, neuropsychiatric and neurodegenerative disorders by delivering protein biomarker signatures for brain dysfunction.
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Texto completo: 1 Índice: IMSEAR Idioma: En Revista: J Biosci Ano de publicação: 2015 Tipo de documento: Article
Texto completo: 1 Índice: IMSEAR Idioma: En Revista: J Biosci Ano de publicação: 2015 Tipo de documento: Article