Computational Proteomics Analysis System (CPAS): An Extensible, Open-Source Analytic System for Evaluating and Publishing Proteomic Data and High Throughput Biological Experiments.

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Authors

Adam Rauch, Matthew Bellew, Jimmy Eng, Matthew Fitzgibbon, Ted Holzman, Peter Hussey, Mark Igra, Brendan Maclean, Chen Wei Lin, Andrea Detter, Ruihua Fang, Vitor Faca, Phil Gafken, Heidi Zhang, Jeffrey Whitaker, David States, Sam Hanash, Amanda Paulovich, and Martin W. McIntosh.

Abstract

The open-source Computational Proteomics Analysis System (CPAS) contains an entire data analysis and management pipeline for Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. CPAS architecture and features, such as a general experiment annotation component, installation software, and data security management, make it useful for collaborative projects across geographical locations and for proteomics laboratories without substantial computational support.

Rauch A, Bellew M, Eng J, Fitzgibbon M, Holzman T, Hussey P, Igra M, Maclean B, Lin CW, Detter A, Fang R, Faca V, Gafken P, Zhang H, Whitaker J, States D, Hanash S, Paulovich A, McIntosh MW: Computational Proteomics Analysis System (CPAS):  An Extensible, Open-Source Analytic System for Evaluating and Publishing Proteomic Data and High Throughput Biological Experiments. Journal of Proteome Research 2006, 5:112-121.

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