Literature DB >> 18067251

False discovery rates and related statistical concepts in mass spectrometry-based proteomics.

Hyungwon Choi1, Alexey I Nesvizhskii.   

Abstract

Development of statistical methods for assessing the significance of peptide assignments to tandem mass spectra obtained using database searching remains an important problem. In the past several years, several different approaches have emerged, including the concept of expectation values, target-decoy strategy, and the probability mixture modeling approach of PeptideProphet. In this work, we provide a background on statistical significance analysis in the field of mass spectrometry-based proteomics, and present our perspective on the current and future developments in this area.

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Year:  2007        PMID： 18067251     DOI： 10.1021/pr700747q

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


  94 in total

1.  Direct maximization of protein identifications from tandem mass spectra.

Authors:  Marina Spivak; Jason Weston; Daniela Tomazela; Michael J MacCoss; William Stafford Noble
Journal:  Mol Cell Proteomics       Date:  2011-11-03       Impact factor: 5.911

2.  Generic comparison of protein inference engines.

Authors:  Manfred Claassen; Lukas Reiter; Michael O Hengartner; Joachim M Buhmann; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2011-11-04       Impact factor: 5.911

3.  Proteomic analysis of a rat pancreatic stellate cell line using liquid chromatography tandem mass spectrometry (LC-MS/MS).

Authors:  Joao A Paulo; Raul Urrutia; Peter A Banks; Darwin L Conwell; Hanno Steen
Journal:  J Proteomics       Date:  2011-09-25       Impact factor: 4.044

4.  Integrated transcriptomic and proteomic analysis of the physiological response of Escherichia coli O157:H7 Sakai to steady-state conditions of cold and water activity stress.

Authors:  Chawalit Kocharunchitt; Thea King; Kari Gobius; John P Bowman; Tom Ross
Journal:  Mol Cell Proteomics       Date:  2011-10-18       Impact factor: 5.911

Review 5.  Generating and navigating proteome maps using mass spectrometry.

Authors:  Christian H Ahrens; Erich Brunner; Ermir Qeli; Konrad Basler; Ruedi Aebersold
Journal:  Nat Rev Mol Cell Biol       Date:  2010-10-14       Impact factor: 94.444

6.  Target-decoy approach and false discovery rate: when things may go wrong.

Authors:  Nitin Gupta; Nuno Bandeira; Uri Keich; Pavel A Pevzner
Journal:  J Am Soc Mass Spectrom       Date:  2011-05-05       Impact factor: 3.109

7.  Proteomic analysis of an immortalized mouse pancreatic stellate cell line identifies differentially-expressed proteins in activated vs nonproliferating cell states.

Authors:  Joao A Paulo; Raul Urrutia; Peter A Banks; Darwin L Conwell; Hanno Steen
Journal:  J Proteome Res       Date:  2011-09-09       Impact factor: 4.466

8.  Rethinking Mass Spectrometry-Based Small Molecule Identification Strategies in Metabolomics.

Authors:  Fumio Matsuda
Journal:  Mass Spectrom (Tokyo)       Date:  2014-08-16

9.  Comparison of MS(2)-only, MSA, and MS(2)/MS(3) methodologies for phosphopeptide identification.

Authors:  Peter J Ulintz; Anastasia K Yocum; Bernd Bodenmiller; Ruedi Aebersold; Philip C Andrews; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2009-02       Impact factor: 4.466

10.  Stable isotope metabolic labeling-based quantitative phosphoproteomic analysis of Arabidopsis mutants reveals ethylene-regulated time-dependent phosphoproteins and putative substrates of constitutive triple response 1 kinase.

Authors:  Zhu Yang; Guangyu Guo; Manyu Zhang; Claire Y Liu; Qin Hu; Henry Lam; Han Cheng; Yu Xue; Jiayang Li; Ning Li
Journal:  Mol Cell Proteomics       Date:  2013-09-16       Impact factor: 5.911
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