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Originally published In Press as doi:10.1074/mcp.M400061-MCP200 on July 21, 2004.
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Molecular & Cellular Proteomics 3:984-997, 2004.
© 2004 by The American Society for Biochemistry and Molecular Biology, Inc.

Research

Informatics Platform for Global Proteomic Profiling and Biomarker Discovery Using Liquid Chromatography-Tandem Mass Spectrometry*,S

Dragan Radulovic{ddagger},§, Salomeh Jelveh||, Soyoung Ryu§, T. Guy Hamilton**,{ddagger}, Eric Foss**, Yongyi Mao§ and Andrew Emili||

From the {ddagger} Department of Statistics, Yale University, New Haven, CT § Department of Mathematics, Florida Atlantic University, Boca Raton, FL || Program in Proteomics and Bioinformatics, Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada ** Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA § School of Information Technology and Engineering, University of Ottawa, Ottawa, ON, Canada

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.

To whom correspondence should be addressed: Dragan Radulovic, Department of Mathematics, Florida Atlantic University, Boca Raton, FL. E-mail: radulovi@fau.edu. Andrew Emili, CH Best Institute, 112 College Street, Toronto, ON, Canada M5G 1L6. Tel.: 416-946-7281; Fax: 416-978-8528; E-mail: andrew.emili{at}utoronto.ca.




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