OpenMS – A Framework for Quantitative HPLC/MS-Based Proteomics
نویسندگان
چکیده
One of the main goals of proteomics research is the discovery of novel diagnostic markers and therapeutic targets. Currently, mass spectrometry is the main platform for analyzing complex protein samples. Lately, HPLC/MS-based approaches have gained considerable interest due to their larger potential for full automation when compared to gel-based techniques. Particularly, multi-dimensional HPLC-MS methods have a great potential as a platform for differential quantification of proteins in complex mixtures. However, computational methods to analyze these automated analyses at a large scale are yet to be developed. The development of these methods should encompass new methods for data reduction, data interpretation, data management and visualization. We propose an algorithmic framework for a fully automated differential analysis of HPLC/MS samples, which goes beyond the currently established pairwise comparison of samples towards a statistically sound analysis of larger sample numbers. In this short paper we outline the framework in its current state and lay out future plans.
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