DIAmeter: matching peptides to data-independent acquisition mass spectrometry data | Zendy

Yang Young Lu | Zendy; Jeff Bilmes | Zendy; Ricard A. RodríguezMias | Zendy; Judit Villén | Zendy; William Stafford Noble | Zendy

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DIAmeter: matching peptides to data-independent acquisition mass spectrometry data

Author(s) -

Yang Young Lu,

Jeff Bilmes,

Ricard A. RodríguezMias,

Judit Villén,

William Stafford Noble

Publication year - 2021

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab284

Subject(s) - computer science , mass spectrometry , data acquisition , matching (statistics) , tandem mass spectrometry , data type , tandem mass tag , software , data mining , information retrieval , chemistry , proteomics , programming language , chromatography , mathematics , biochemistry , statistics , gene , quantitative proteomics

Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a 'spectral library'), but this approach is expensive because the libraries do not typically generalize well across laboratories.

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