The recent advances in proteomic instrumentation, methods and informatics have created exciting opportunities in all fields of diabetes research. The information on protein identification and structure provided by mass spectrometry is applicable to nearly all aspects of diabetes and its complications. Mass spectrometry-based proteomics has accelerated the identification of posttranslational modifications, including phosphorylation-site mapping, identification of protein-protein interactions, and changes in protein abundance or compartmentalization, just to name a few examples. However, the rapid rates of growth and change in proteomic technologies have also led to challenges in the translation and availability of these technologies to researchers, from new postdoctoral 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 appropriate experimental 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, mass spectrometry-based proteomics is a multi-step process, and study design, from the perspectives of mass spectrometry data acquisition and interpretation, plays an important role in experimental success. The overall objective of the Proteomics Core is to provide Joslin researchers with assistance through the workflow of proteomics studies, including experimental design, sample preparation, 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 of proteomics data into the results database.
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