Literature DB >> 26685308

MSAcquisitionSimulator: data-dependent acquisition simulator for LC-MS shotgun proteomics.

Dennis Goldfarb1, Wei Wang2, Michael B Major3.   

Abstract

UNLABELLED: Data-dependent acquisition (DDA) is the most common method used to control the acquisition process of shotgun proteomics experiments. While novel DDA approaches have been proposed, their evaluation is made difficult by the need of programmatic control of a mass spectrometer. An alternative is in silico analysis, for which suitable software has been unavailable. To meet this need, we have developed MSAcquisitionSimulator-a collection of C ++ programs for simulating ground truth LC-MS data and the subsequent application of custom DDA algorithms. It provides an opportunity for researchers to test, refine and evaluate novel DDA algorithms prior to implementation on a mass spectrometer.
AVAILABILITY AND IMPLEMENTATION: The software is freely available from its Github repository http://www.github.com/DennisGoldfarb/MSAcquisitionSimulator/ which contains further documentation and usage instructions. CONTACT: weiwang@cs.ucla.edu or ben_major@med.unc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 26685308      PMCID: PMC4894284          DOI: 10.1093/bioinformatics/btv745

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

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Authors:  Andrew B Noyce; Rob Smith; James Dalgleish; Ryan M Taylor; K C Erb; Nozomu Okuda; John T Prince
Journal:  J Proteome Res       Date:  2013-10-03       Impact factor: 4.466

2.  MSSimulator: Simulation of mass spectrometry data.

Authors:  Chris Bielow; Stephan Aiche; Sandro Andreotti; Knut Reinert
Journal:  J Proteome Res       Date:  2011-04-28       Impact factor: 4.466

3.  More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS.

Authors:  Annette Michalski; Juergen Cox; Matthias Mann
Journal:  J Proteome Res       Date:  2011-02-28       Impact factor: 4.466

4.  JAMSS: proteomics mass spectrometry simulation in Java.

Authors:  Rob Smith; John T Prince
Journal:  Bioinformatics       Date:  2014-11-03       Impact factor: 6.937

5.  Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data.

Authors:  Oliver Serang; Michael J MacCoss; William Stafford Noble
Journal:  J Proteome Res       Date:  2010-10-01       Impact factor: 4.466

6.  Directed sample interrogation utilizing an accurate mass exclusion-based data-dependent acquisition strategy (AMEx).

Authors:  Emily L Rudomin; Steven A Carr; Jacob D Jaffe
Journal:  J Proteome Res       Date:  2009-06       Impact factor: 4.466

7.  Nonredundant mass spectrometry: a strategy to integrate mass spectrometry acquisition and analysis.

Authors:  Alexander Scherl; Patrice Francois; Véronique Converset; Manuela Bento; Jennifer A Burgess; Jean-Charles Sanchez; Denis F Hochstrasser; Jacques Schrenzel; Garry L Corthals
Journal:  Proteomics       Date:  2004-04       Impact factor: 3.984

8.  Optimal precursor ion selection for LC-MALDI MS/MS.

Authors:  Alexandra Zerck; Eckhard Nordhoff; Hans Lehrach; Knut Reinert
Journal:  BMC Bioinformatics       Date:  2013-02-18       Impact factor: 3.169

9.  A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Authors:  Johannes Graumann; Richard A Scheltema; Yong Zhang; Jürgen Cox; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2011-12-13       Impact factor: 5.911

10.  LC-MSsim--a simulation software for liquid chromatography mass spectrometry data.

Authors:  Ole Schulz-Trieglaff; Nico Pfeifer; Clemens Gröpl; Oliver Kohlbacher; Knut Reinert
Journal:  BMC Bioinformatics       Date:  2008-10-08       Impact factor: 3.169

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  2 in total

1.  Accelerating Lipidomic Method Development through in Silico Simulation.

Authors:  Paul D Hutchins; Jason D Russell; Joshua J Coon
Journal:  Anal Chem       Date:  2019-07-25       Impact factor: 6.986

2.  In Silico Optimization of Mass Spectrometry Fragmentation Strategies in Metabolomics.

Authors:  Joe Wandy; Vinny Davies; Justin J J van der Hooft; Stefan Weidt; Rónán Daly; Simon Rogers
Journal:  Metabolites       Date:  2019-10-09
  2 in total

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