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Informatics platform for global proteomic profiling and biomarker discovery using liquid chromatography-tandem mass spectrometry
Authors:Radulovic Dragan  Jelveh Salomeh  Ryu Soyoung  Hamilton T Guy  Foss Eric  Mao Yongyi  Emili Andrew
Affiliation:Department of Statistics, Yale University, New Haven, CT, USA. radulovi@fau.edu
Abstract:We have developed an integrated suite of algorithms, statistical methods, and computer applications to support large-scale LC-MS-based gel-free shotgun profiling of complex protein mixtures using basic experimental procedures. The programs automatically detect and quantify large numbers of peptide peaks in feature-rich ion mass chromatograms, compensate for spurious fluctuations in peptide signal intensities and retention times, and reliably match related peaks across many different datasets. Application of this toolkit markedly facilitates pattern recognition and biomarker discovery in global comparative proteomic studies, simplifying mechanistic investigation of physiological responses and the detection of proteomic signatures of disease.
Keywords:
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