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Quality meets quantity – quality control, data standards and repositories
Author(s) -
Eisenacher Martin,
Schnabel Anke,
Stephan Christian
Publication year - 2011
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.201000441
Subject(s) - standardization , quality (philosophy) , documentation , control (management) , data quality , computer science , identification (biology) , quality assurance , data science , data sharing , process management , risk analysis (engineering) , engineering , business , external quality assessment , operations management , medicine , metric (unit) , philosophy , botany , alternative medicine , epistemology , pathology , artificial intelligence , biology , programming language , operating system
In recent years, standardization and quality control have become important key points in industry, e.g. in drug discovery and for developing medical products. Is quality control in academic Proteomics a minor problem nowadays, where standard data formats and public repositories for data sharing exist? In this article, it is discussed how standard formats and repositories already support the documentation of quality control criteria in protein identification and quantification, and what has to be improved in the future: It is stated that the Proteomics community (represented by a group like the Proteomics Standards Initiative) will have to define a minimum document regarding quality control and to extend existing standards with additional quality control criteria enabling a substantial and standardized quality control process.