Literature DB >> 33950500

Establishing a Custom-Fit Data-Independent Acquisition Method for Label-Free Proteomics.

Britta Eggers1,2, Martin Eisenacher3,4, Katrin Marcus3,4, Julian Uszkoreit3,4.   

Abstract

Data-independent acquisition (DIA) has recently developed as a powerful tool to enhance the quantification of peptides and proteins within a variety of sample types, by overcoming the stochastic nature of classical data-dependent approaches, as well as by enabling the identification of all peptides detected in a mass spectrometric event. Here, we describe a workflow for the establishment of a sample-fitting DIA method using Spectronaut Pulsar X (Biognosys, Switzerland).

Keywords:  Data-independent acquisition; Label-free quantification; Spectral library generation

Year:  2021        PMID： 33950500     DOI： 10.1007/978-1-0716-1024-4_22

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  8 in total

1.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

Authors:  Brendan MacLean; Daniela M Tomazela; Nicholas Shulman; Matthew Chambers; Gregory L Finney; Barbara Frewen; Randall Kern; David L Tabb; Daniel C Liebler; Michael J MacCoss
Journal:  Bioinformatics       Date:  2010-02-09       Impact factor: 6.937

Review 2.  BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication.

Authors:  Michael Turewicz; Michael Kohl; Maike Ahrens; Gerhard Mayer; Julian Uszkoreit; Wael Naboulsi; Thilo Bracht; Dominik A Megger; Barbara Sitek; Katrin Marcus; Martin Eisenacher
Journal:  J Biotechnol       Date:  2017-06-09       Impact factor: 3.307

3.  OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data.

Authors:  Hannes L Röst; George Rosenberger; Pedro Navarro; Ludovic Gillet; Saša M Miladinović; Olga T Schubert; Witold Wolski; Ben C Collins; Johan Malmström; Lars Malmström; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2014-03       Impact factor: 54.908

4.  OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

Authors:  Hannes L Röst; Timo Sachsenberg; Stephan Aiche; Chris Bielow; Hendrik Weisser; Fabian Aicheler; Sandro Andreotti; Hans-Christian Ehrlich; Petra Gutenbrunner; Erhan Kenar; Xiao Liang; Sven Nahnsen; Lars Nilse; Julianus Pfeuffer; George Rosenberger; Marc Rurik; Uwe Schmitt; Johannes Veit; Mathias Walzer; David Wojnar; Witold E Wolski; Oliver Schilling; Jyoti S Choudhary; Lars Malmström; Ruedi Aebersold; Knut Reinert; Oliver Kohlbacher
Journal:  Nat Methods       Date:  2016-08-30       Impact factor: 28.547

5.  Protein Inference Using PIA Workflows and PSI Standard File Formats.

Authors:  Julian Uszkoreit; Yasset Perez-Riverol; Britta Eggers; Katrin Marcus; Martin Eisenacher
Journal:  J Proteome Res       Date:  2018-12-05       Impact factor: 4.466

6.  DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics.

Authors:  Chih-Chiang Tsou; Dmitry Avtonomov; Brett Larsen; Monika Tucholska; Hyungwon Choi; Anne-Claude Gingras; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2015-01-19       Impact factor: 28.547

7.  Reproducibility, Specificity and Accuracy of Relative Quantification Using Spectral Library-based Data-independent Acquisition.

Authors:  Katalin Barkovits; Sandra Pacharra; Kathy Pfeiffer; Simone Steinbach; Martin Eisenacher; Katrin Marcus; Julian Uszkoreit
Journal:  Mol Cell Proteomics       Date:  2019-11-07       Impact factor: 5.911

8.  Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.

Authors:  Roland Bruderer; Oliver M Bernhardt; Tejas Gandhi; Yue Xuan; Julia Sondermann; Manuela Schmidt; David Gomez-Varela; Lukas Reiter
Journal:  Mol Cell Proteomics       Date:  2017-10-25       Impact factor: 5.911
  8 in total

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