The recent advances in proteomic instrumentation, methods and informatics have created excitingopportunities in all fields of diabetes research. The information on protein identification andstructure provided by mass spectrometry is applicable to nearly all aspects of diabetes and itscomplications. Mass spectrometry-based proteomics has accelerated the identification of posttranslationalmodifications, including phosphorylation-site mapping, identification of protein-proteininteractions, and changes in protein abundance or compartmentalization, just to name a fewexamples. However, the rapid rates of growth and change in proteomic technologies have also ledto challenges in the translation and availability of these technologies to researchers, from newpostdoctoral research fellows to established investigators who are not directly involved in this field.Although many of the fundamental principles of mass spectrometry are relatively straightforward,successful mass spectrometry-based proteomic analysis requires the combination of appropriateexperimental design, access to state-of-the-art instrumentation, rigorous analysis of spectral data,and for some studies, bioinformatics tools to manage and interpret large datasets. Indeed, massspectrometry-based proteomics is a multi-step process, and study design, from the perspectives ofmass spectrometry data acquisition and interpretation, plays an important role in experimentalsuccess. The overall objective of the Proteomics Core is to provide Joslin researchers withassistance through the workflow of proteomics studies, including experimental design, samplepreparation, mass spectrometric analysis, data analysis and interpretation, and bioinformatic tools.The specific objectives of Joslin's Proteomics Core are the following:1) To assist and provide training in experimental design for proteomics studies.2) To provide routine and custom mass spectroscopy-based proteomic analyses.3) To assist with mass spectra analysis, interpretation, and database matching.4) To develop a results database and incorporate access to bioinformatic tools for the analysis ofproteomics data into the results database.
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