Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics | Zendy

Kelli G. Kline | Zendy; Gregory L. Finney | Zendy; C. C. Wu | Zendy

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Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics

Author(s) -

Kelli G. Kline,

Gregory L. Finney,

C. C. Wu

Publication year - 2009

Publication title -

briefings in functional genomics and proteomics

Language(s) - English

Resource type - Journals

eISSN - 1477-4062

pISSN - 1473-9550

DOI - 10.1093/bfgp/elp008

Subject(s) - computational biology , biology , proteomics , shotgun proteomics , shotgun , pipeline (software) , biomarker discovery , bioinformatics , computer science , genetics , gene , programming language

The ultimate goal of most shotgun proteomic pipelines is the discovery of novel biomarkers to direct the development of quantitative diagnostics for the detection and treatment of disease. Differential comparisons of biological samples identify candidate peptides that can serve as proxys of candidate proteins. While these discovery approaches are robust and fairly comprehensive, they have relatively low throughput. When merged with targeted mass spectrometry, this pipeline can fuel hypothesis-driven studies and the development of novel diagnostics and therapeutics.

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