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Anatomy and evolution of database search engines—a central component of mass spectrometry based proteomic workflows
Author(s) -
Verheggen Kenneth,
Ræder Helge,
Berven Frode S.,
Martens Lennart,
Barsnes Harald,
Vaudel Marc
Publication year - 2017
Publication title -
mass spectrometry reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 126
eISSN - 1098-2787
pISSN - 0277-7037
DOI - 10.1002/mas.21543
Subject(s) - database search engine , workflow , sequence database , chemistry , database , mass spectrometry , component (thermodynamics) , identification (biology) , information retrieval , complement (music) , tandem mass spectrometry , sequence (biology) , computer science , computational biology , search engine , data mining , chromatography , biology , physics , thermodynamics , biochemistry , botany , complementation , gene , phenotype
Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines.