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Preprocessing of tandem mass spectrometric data to support automatic protein identification
Author(s) -
Gentzel Marc,
Köcher Thomas,
Ponnusamy Saravanan,
Wilm Matthias
Publication year - 2003
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.200300486
Subject(s) - preprocessor , fragment (logic) , computer science , tandem mass spectrometry , identification (biology) , sequence database , database search engine , tandem , data pre processing , reliability (semiconductor) , mass spectrometry , data mining , conjunction (astronomy) , computational biology , chemistry , database , search engine , artificial intelligence , chromatography , information retrieval , biology , algorithm , biochemistry , engineering , physics , power (physics) , quantum mechanics , botany , astronomy , gene , aerospace engineering
Liquid chromatography tandem mass spectrometry is a major tool for identifying proteins. The fragment spectra of peptides can be interpreted automatically in conjunction with a sequence database search. With the development of powerful automatic search engines, research now focuses on optimizing the result returned from database searches. We present a series of preprocessing steps for fragment spectra to increase the accuracy and specificity of automatic database searches. After processing, the correct amino acid sequences from the database can be related better to the fragment spectra. This increases the sensitivity and reliability of protein identifications, especially with very large genomic databanks, and can be important for the systematic characterization of post‐translational modifications.