Literature DB >> 26616598

Spectral library searching in proteomics.

Johannes Griss1,2.   

Abstract

Spectral library searching has become a mature method to identify tandem mass spectra in proteomics data analysis. This review provides a comprehensive overview of available spectral library search engines and highlights their distinct features. Additionally, resources providing spectral libraries are summarized and tools presented that extend experimental spectral libraries by simulating spectra. Finally, spectrum clustering algorithms are discussed that utilize the same spectrum-to-spectrum matching algorithms as spectral library search engines and allow novel methods to analyse proteomics data.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Bioinformatics; Spectral libraries; Spectral library searching; Spectrum clustering

Mesh:

Substances:

Year:  2016        PMID: 26616598     DOI: 10.1002/pmic.201500296

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  15 in total

1.  2018 YPIC Challenge: A Case Study in Characterizing an Unknown Protein Sample.

Authors:  Lindsay Pino; Andy Lin; Wout Bittremieux
Journal:  J Proteome Res       Date:  2019-10-07       Impact factor: 4.466

2.  Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data.

Authors:  Karin Schork; Katharina Podwojski; Michael Turewicz; Christian Stephan; Martin Eisenacher
Journal:  Methods Mol Biol       Date:  2021

3.  Searching for Small Molecules with an Atomic Sort.

Authors:  Brendan M Duggan; Reiko Cullum; William Fenical; Luis A Amador; Abimael D Rodríguez; James J La Clair
Journal:  Angew Chem Int Ed Engl       Date:  2019-12-02       Impact factor: 15.336

4.  The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

Authors:  Juan Antonio Vizcaíno; Peter Kubiniok; Kevin A Kovalchik; Qing Ma; Jérôme D Duquette; Ian Mongrain; Eric W Deutsch; Bjoern Peters; Alessandro Sette; Isabelle Sirois; Etienne Caron
Journal:  Mol Cell Proteomics       Date:  2019-11-19       Impact factor: 5.911

Review 5.  Identification of small molecules using accurate mass MS/MS search.

Authors:  Tobias Kind; Hiroshi Tsugawa; Tomas Cajka; Yan Ma; Zijuan Lai; Sajjan S Mehta; Gert Wohlgemuth; Dinesh Kumar Barupal; Megan R Showalter; Masanori Arita; Oliver Fiehn
Journal:  Mass Spectrom Rev       Date:  2017-04-24       Impact factor: 10.946

Review 6.  A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts.

Authors:  Joshua A Klein; Joseph Zaia
Journal:  Biochemistry       Date:  2019-12-31       Impact factor: 3.162

7.  Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing.

Authors:  Wout Bittremieux; Pieter Meysman; William Stafford Noble; Kris Laukens
Journal:  J Proteome Res       Date:  2018-09-13       Impact factor: 4.466

Review 8.  Expanding the Use of Spectral Libraries in Proteomics.

Authors:  Eric W Deutsch; Yasset Perez-Riverol; Robert J Chalkley; Mathias Wilhelm; Stephen Tate; Timo Sachsenberg; Mathias Walzer; Lukas Käll; Bernard Delanghe; Sebastian Böcker; Emma L Schymanski; Paul Wilmes; Viktoria Dorfer; Bernhard Kuster; Pieter-Jan Volders; Nico Jehmlich; Johannes P C Vissers; Dennis W Wolan; Ana Y Wang; Luis Mendoza; Jim Shofstahl; Andrew W Dowsey; Johannes Griss; Reza M Salek; Steffen Neumann; Pierre-Alain Binz; Henry Lam; Juan Antonio Vizcaíno; Nuno Bandeira; Hannes Röst
Journal:  J Proteome Res       Date:  2018-10-11       Impact factor: 4.466

9.  Software Options for the Analysis of MS-Proteomic Data.

Authors:  Avinash Yadav; Federica Marini; Alessandro Cuomo; Tiziana Bonaldi
Journal:  Methods Mol Biol       Date:  2021

10.  Future Prospects of Spectral Clustering Approaches in Proteomics.

Authors:  Yasset Perez-Riverol; Juan Antonio Vizcaíno; Johannes Griss
Journal:  Proteomics       Date:  2018-07       Impact factor: 3.984

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