Literature DB >> 21325204

The potential cost of high-throughput proteomics.

Forest M White1.   

Abstract

Improvements in speed and mass accuracy of mass spectrometers revolutionized proteomics, with high-throughput proteomics enabling the profiling of complete proteomes and thousands of posttranslational modification sites. The limits of high-throughput proteomics are constantly pushed to new frontiers, and mass spectrometry-based proteomics may eventually permit the analysis of protein expression profiles in less than a day. Increased data acquisition speed has led to a dramatic increase in the total number of tandem mass spectrometry (MS/MS) spectra, such that millions of MS/MS spectra are now acquired in a given set of analyses. Many of these spectra are insufficiently validated; instead, statistical tools are commonly used to estimate false-positive or false-discovery rates for these data sets. Many laboratories may not realize the costs associated with using these widely available, but minimally validated, data sets. The costs associated with use of these data can include missed opportunities for biological insight, the pollution of databases with increasing numbers of false-positive identifications, and time spent by biologists investigating false leads, resulting in a lack of faith in proteomics data. Improved strategies for data validation need to be implemented, along with a change in the culture of high-throughput proteomics, linking proteomics closer to biology.

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Year:  2011        PMID: 21325204     DOI: 10.1126/scisignal.2001813

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  17 in total

Review 1.  Phosphoproteomic analysis: an emerging role in deciphering cellular signaling in human embryonic stem cells and their differentiated derivatives.

Authors:  Brian T D Tobe; Junjie Hou; Andrew M Crain; Ilyas Singec; Evan Y Snyder; Laurence M Brill
Journal:  Stem Cell Rev Rep       Date:  2012-03       Impact factor: 5.739

2.  Simultaneous Quantification of Protein Expression and Modifications by Top-down Targeted Proteomics: A Case of the Sarcomeric Subproteome.

Authors:  Ziqing Lin; Liming Wei; Wenxuan Cai; Yanlong Zhu; Trisha Tucholski; Stanford D Mitchell; Wei Guo; Stephen P Ford; Gary M Diffee; Ying Ge
Journal:  Mol Cell Proteomics       Date:  2018-12-27       Impact factor: 5.911

3.  Design and application of a data-independent precursor and product ion repository.

Authors:  Konstantinos Thalassinos; Johannes P C Vissers; Stefan Tenzer; Yishai Levin; J Will Thompson; David Daniel; Darrin Mann; Mark R DeLong; M Arthur Moseley; Antoine H America; Andrew K Ottens; Greg S Cavey; Georgios Efstathiou; James H Scrivens; James I Langridge; Scott J Geromanos
Journal:  J Am Soc Mass Spectrom       Date:  2012-07-31       Impact factor: 3.109

4.  Defining, comparing, and improving iTRAQ quantification in mass spectrometry proteomics data.

Authors:  Lina Hultin-Rosenberg; Jenny Forshed; Rui M M Branca; Janne Lehtiö; Henrik J Johansson
Journal:  Mol Cell Proteomics       Date:  2013-03-07       Impact factor: 5.911

Review 5.  System level dynamics of post-translational modifications.

Authors:  Aaron S Gajadhar; Forest M White
Journal:  Curr Opin Biotechnol       Date:  2014-01-15       Impact factor: 9.740

6.  Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Authors:  Jian-Ying Zhou; Lijun Chen; Bai Zhang; Yuan Tian; Tao Liu; Stefani N Thomas; Li Chen; Michael Schnaubelt; Emily Boja; Tara Hiltke; Christopher R Kinsinger; Henry Rodriguez; Sherri R Davies; Shunqiang Li; Jacqueline E Snider; Petra Erdmann-Gilmore; David L Tabb; R Reid Townsend; Matthew J Ellis; Karin D Rodland; Richard D Smith; Steven A Carr; Zhen Zhang; Daniel W Chan; Hui Zhang
Journal:  J Proteome Res       Date:  2017-11-16       Impact factor: 4.466

Review 7.  Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing.

Authors:  Mak A Saito; Erin M Bertrand; Megan E Duffy; David A Gaylord; Noelle A Held; William Judson Hervey; Robert L Hettich; Pratik D Jagtap; Michael G Janech; Danie B Kinkade; Dagmar H Leary; Matthew R McIlvin; Eli K Moore; Robert M Morris; Benjamin A Neely; Brook L Nunn; Jaclyn K Saunders; Adam I Shepherd; Nicholas I Symmonds; David A Walsh
Journal:  J Proteome Res       Date:  2019-03-12       Impact factor: 4.466

8.  Computer aided manual validation of mass spectrometry-based proteomic data.

Authors:  Timothy G Curran; Bryan D Bryson; Michael Reigelhaupt; Hannah Johnson; Forest M White
Journal:  Methods       Date:  2013-03-13       Impact factor: 3.608

Review 9.  Studying Cellular Signal Transduction with OMIC Technologies.

Authors:  Benjamin D Landry; David C Clarke; Michael J Lee
Journal:  J Mol Biol       Date:  2015-08-03       Impact factor: 5.469

10.  UniProtKB amid the turmoil of plant proteomics research.

Authors:  Michel Schneider; Sylvain Poux
Journal:  Front Plant Sci       Date:  2012-12-06       Impact factor: 5.753

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