Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments
Author(s) -
Marc Kirchner,
Wiebke Timm,
Peying Fong,
Philine Wangemann,
Hanno Steen
Publication year - 2010
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btq036
Subject(s) - fragmentation (computing) , analyte , mass spectrometry , computer science , software , mass spectrum , generalization , algorithm , tandem mass spectrometry , data mining , biological system , chemistry , mathematics , chromatography , mathematical analysis , programming language , operating system , biology
Mass spectrometry (MS) has become the method of choice for protein/peptide sequence and modification analysis. The technology employs a two-step approach: ionized peptide precursor masses are detected, selected for fragmentation, and the fragment mass spectra are collected for computational analysis. Current precursor selection schemes are based on data- or information-dependent acquisition (DDA/IDA), where fragmentation mass candidates are selected by intensity and are subsequently included in a dynamic exclusion list to avoid constant refragmentation of highly abundant species. DDA/IDA methods do not exploit valuable information that is contained in the fractional mass of high-accuracy precursor mass measurements delivered by current instrumentation.
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