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Science, marketing and wishful thinking in quantitative proteomics
Author(s) -
Hackett Murray
Publication year - 2008
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200800358
Subject(s) - data science , wishful thinking , computer science , sampling (signal processing) , proteomics , scale (ratio) , psychology , biology , social psychology , geography , biochemistry , filter (signal processing) , computer vision , gene , cartography
In a recent editorial ( J. Proteome Res. 2007, 6 , 1633) and elsewhere questions have been raised regarding the lack of attention paid to good analytical practice with respect to the reporting of quantitative results in proteomics. Using those comments as a starting point, several issues are discussed that relate to the challenges involved in achieving adequate sampling with MS‐based methods in order to generate valid data for large‐scale studies. The discussion touches on the relationships that connect sampling depth and the power to detect protein abundance change, conflict of interest, and strategies to overcome bureaucratic obstacles that impede the use of peer‐to‐peer technologies for transfer and storage of large data files generated in such experiments.