Literature DB >> 17513294

The Association of Biomolecular Resource Facilities Proteomics Research Group 2006 study: relative protein quantitation.

Christoph W Turck1, Arnold M Falick, Jeffrey A Kowalak, William S Lane, Kathryn S Lilley, Brett S Phinney, Susan T Weintraub, H Ewa Witkowska, Nathan A Yates.   

Abstract

The determination of differences in relative protein abundance is a critical aspect of proteomics research that is increasingly used to answer diverse biological questions. The Association of Biomolecular Resource Facilities Proteomics Research Group 2006 study was a quantitative proteomics project in which the aim was to determine the identity and the relative amounts of eight proteins in two mixtures. There are numerous methodologies available to study the relative abundance of proteins between samples, but to date, there are few examples of studies that have compared these different approaches. For the 2006 Proteomics Research Group study, there were 52 participants who used a wide variety of gel electrophoresis-, HPLC-, and mass spectrometry-based methods for relative quantitation. The quantitative data arising from this study were evaluated along with several other experimental details relevant to the methodologies used.

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Year:  2007        PMID: 17513294     DOI: 10.1074/mcp.M700165-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  37 in total

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Authors:  Christopher R Kinsinger; James Apffel; Mark Baker; Xiaopeng Bian; Christoph H Borchers; Ralph Bradshaw; Mi-Youn Brusniak; Daniel W Chan; Eric W Deutsch; Bruno Domon; Jeff Gorman; Rudolf Grimm; William Hancock; Henning Hermjakob; David Horn; Christie Hunter; Patrik Kolar; Hans-Joachim Kraus; Hanno Langen; Rune Linding; Robert L Moritz; Gilbert S Omenn; Ron Orlando; Akhilesh Pandey; Peipei Ping; Amir Rahbar; Robert Rivers; Sean L Seymour; Richard J Simpson; Douglas Slotta; Richard D Smith; Stephen E Stein; David L Tabb; Danilo Tagle; John R Yates; Henry Rodriguez
Journal:  Mol Cell Proteomics       Date:  2011-11-03       Impact factor: 5.911

2.  Distinct energy metabolism of auditory and vestibular sensory epithelia revealed by quantitative mass spectrometry using MS2 intensity.

Authors:  Kateri J Spinelli; John E Klimek; Phillip A Wilmarth; Jung-Bum Shin; Dongseok Choi; Larry L David; Peter G Gillespie
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-17       Impact factor: 11.205

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

4.  Quantitative proteomics in plants: choices in abundance.

Authors:  Jay J Thelen; Scott C Peck
Journal:  Plant Cell       Date:  2007-11-30       Impact factor: 11.277

5.  Application of label-free quantitative peptidomics for the identification of urinary biomarkers of kidney chronic allograft dysfunction.

Authors:  Luis F Quintana; Josep M Campistol; Maria P Alcolea; Elisenda Bañon-Maneus; Amandaé Sol-González; Pedro R Cutillas
Journal:  Mol Cell Proteomics       Date:  2009-04-07       Impact factor: 5.911

6.  Precision, proteome coverage, and dynamic range of Arabidopsis proteome profiling using (15)N metabolic labeling and label-free approaches.

Authors:  Borjana Arsova; Henrik Zauber; Waltraud X Schulze
Journal:  Mol Cell Proteomics       Date:  2012-05-05       Impact factor: 5.911

Review 7.  Gene expression analysis, proteomics, and network discovery.

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Journal:  Plant Physiol       Date:  2009-12-11       Impact factor: 8.340

8.  A statistical model for iTRAQ data analysis.

Authors:  Elizabeth G Hill; John H Schwacke; Susana Comte-Walters; Elizabeth H Slate; Ann L Oberg; Jeanette E Eckel-Passow; Terry M Therneau; Kevin L Schey
Journal:  J Proteome Res       Date:  2008-06-26       Impact factor: 4.466

9.  ABRF-PRG07: advanced quantitative proteomics study.

Authors:  Arnold M Falick; William S Lane; Kathryn S Lilley; Michael J MacCoss; Brett S Phinney; Nicholas E Sherman; Susan T Weintraub; H Ewa Witkowska; Nathan A Yates
Journal:  J Biomol Tech       Date:  2011-04

10.  A HUPO test sample study reveals common problems in mass spectrometry-based proteomics.

Authors:  Alexander W Bell; Eric W Deutsch; Catherine E Au; Robert E Kearney; Ron Beavis; Salvatore Sechi; Tommy Nilsson; John J M Bergeron
Journal:  Nat Methods       Date:  2009-06       Impact factor: 28.547

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