Literature DB >> 18173218

An assessment of software solutions for the analysis of mass spectrometry based quantitative proteomics data.

Lukas N Mueller1, Mi-Youn Brusniak, D R Mani, Ruedi Aebersold.   

Abstract

Over the past decade, a series of experimental strategies for mass spectrometry based quantitative proteomics and corresponding computational methodology for the processing of the resulting data have been generated. We provide here an overview of the main quantification principles and available software solutions for the analysis of data generated by liquid chromatography coupled to mass spectrometry (LC-MS). Three conceptually different methods to perform quantitative LC-MS experiments have been introduced. In the first, quantification is achieved by spectral counting, in the second via differential stable isotopic labeling, and in the third by using the ion current in label-free LC-MS measurements. We discuss here advantages and challenges of each quantification approach and assess available software solutions with respect to their instrument compatibility and processing functionality. This review therefore serves as a starting point for researchers to choose an appropriate software solution for quantitative proteomic experiments based on their experimental and analytical requirements.

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Year:  2008        PMID: 18173218     DOI: 10.1021/pr700758r

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  146 in total

1.  Label-free peptide profiling of Orbitrap™ full mass spectra.

Authors:  Mark K Titulaer; Dominique de Costa; Christoph Stingl; Lennard J Dekker; Peter Ae Sillevis Smitt; Theo M Luider
Journal:  BMC Res Notes       Date:  2011-01-27

2.  msCompare: a framework for quantitative analysis of label-free LC-MS data for comparative candidate biomarker studies.

Authors:  Berend Hoekman; Rainer Breitling; Frank Suits; Rainer Bischoff; Peter Horvatovich
Journal:  Mol Cell Proteomics       Date:  2012-02-07       Impact factor: 5.911

3.  Extending the dynamic range of label-free mass spectrometric quantification of affinity purifications.

Authors:  Wolfgang Bildl; Alexander Haupt; Catrin S Müller; Martin L Biniossek; Jörg Oliver Thumfart; Björn Hüber; Bernd Fakler; Uwe Schulte
Journal:  Mol Cell Proteomics       Date:  2011-11-08       Impact factor: 5.911

Review 4.  Decoding signalling networks by mass spectrometry-based proteomics.

Authors:  Chunaram Choudhary; Matthias Mann
Journal:  Nat Rev Mol Cell Biol       Date:  2010-05-12       Impact factor: 94.444

5.  Relative, label-free protein quantitation: spectral counting error statistics from nine replicate MudPIT samples.

Authors:  Bret Cooper; Jian Feng; Wesley M Garrett
Journal:  J Am Soc Mass Spectrom       Date:  2010-05-06       Impact factor: 3.109

6.  Investigation of the ovarian and prostate cancer peptidome for candidate early detection markers using a novel nanoparticle biomarker capture technology.

Authors:  Claudia Fredolini; Francesco Meani; Alessandra Luchini; Weidong Zhou; Paul Russo; Mark Ross; Alexis Patanarut; Davide Tamburro; Guido Gambara; David Ornstein; Franco Odicino; Monica Ragnoli; Antonella Ravaggi; Francesco Novelli; Devis Collura; Leonardo D'Urso; Giovanni Muto; Claudio Belluco; Sergio Pecorelli; Lance Liotta; Emanuel F Petricoin
Journal:  AAPS J       Date:  2010-06-12       Impact factor: 4.009

7.  Peptide identification from mixture tandem mass spectra.

Authors:  Jian Wang; Josué Pérez-Santiago; Jonathan E Katz; Parag Mallick; Nuno Bandeira
Journal:  Mol Cell Proteomics       Date:  2010-03-27       Impact factor: 5.911

8.  Proteome-wide dysregulation by PRA1 depletion delineates a role of PRA1 in lipid transport and cell migration.

Authors:  Hao-Ping Liu; Chih-Ching Wu; Hung-Yi Kao; Yi-Chuan Huang; Ying Liang; Chia-Chun Chen; Jau-Song Yu; Yu-Sun Chang
Journal:  Mol Cell Proteomics       Date:  2010-06-30       Impact factor: 5.911

9.  DeMix-Q: Quantification-Centered Data Processing Workflow.

Authors:  Bo Zhang; Lukas Käll; Roman A Zubarev
Journal:  Mol Cell Proteomics       Date:  2016-01-04       Impact factor: 5.911

10.  Quantification of isotopically overlapping deamidated and 18o-labeled peptides using isotopic envelope mixture modeling.

Authors:  Surendra Dasari; Phillip A Wilmarth; Ashok P Reddy; Lucinda J G Robertson; Srinivasa R Nagalla; Larry L David
Journal:  J Proteome Res       Date:  2009-03       Impact factor: 4.466

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