Originally published In Press as doi:10.1074/mcp.T600049-MCP200 on December 12, 2006.
Molecular & Cellular Proteomics 6:527-536, 2007.
© 2007 by The American Society for Biochemistry and Molecular Biology, Inc.
Technology
EBP, a Program for Protein Identification Using Multiple Tandem Mass Spectrometry Datasets*,S
Thomas S. Price ,
Margaret B. Lucitt ,
Weichen Wu ,
David J. Austin ,
Angel Pizarro ,
Anastasia K. Yocum ,
Ian A. Blair ,¶,
Garret A. FitzGerald ,|| and
Tilo Grosser ,**
From the Institute for Translational Medicine and Therapeutics and Center for Cancer Pharmacology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
MS/MS combined with database search methods can identify the proteins present in complex mixtures. High throughput methods that infer probable peptide sequences from enzymatically digested protein samples create a challenge in how best to aggregate the evidence for candidate proteins. Typically the results of multiple technical and/or biological replicate experiments must be combined to maximize sensitivity. We present a statistical method for estimating probabilities of protein expression that integrates peptide sequence identifications from multiple search algorithms and replicate experimental runs. The method was applied to create a repository of 797 non-homologous zebrafish (Danio rerio) proteins, at an empirically validated false identification rate under 1%, as a resource for the development of targeted quantitative proteomics assays. We have implemented this statistical method as an analytic module that can be integrated with an existing suite of open-source proteomics software.
** To whom correspondence should be addressed: The Inst. for Translational Medicine and Therapeutics, University of Pennsylvania, 809 BRB II/III, 421 Curie Blvd., Philadelphia, PA 19104. Tel.: 215-573-7600; Fax: 215-573-9004; E-mail: tilo{at}spirit.gcrc.upenn.edu

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Copyright © 2007 by the American Society for Biochemistry and Molecular Biology.
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