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Items: 1 to 20 of 119

1.

Rapid and accurate peptide identification from tandem mass spectra.

Park CY, Klammer AA, Käll L, MacCoss MJ, Noble WS.

J Proteome Res. 2008 Jul;7(7):3022-7. doi: 10.1021/pr800127y. Epub 2008 May 28.

2.

Faster SEQUEST searching for peptide identification from tandem mass spectra.

Diament BJ, Noble WS.

J Proteome Res. 2011 Sep 2;10(9):3871-9. doi: 10.1021/pr101196n. Epub 2011 Jul 29.

3.

Semi-supervised learning for peptide identification from shotgun proteomics datasets.

Käll L, Canterbury JD, Weston J, Noble WS, MacCoss MJ.

Nat Methods. 2007 Nov;4(11):923-5. Epub 2007 Oct 21.

PMID:
17952086
4.

Semisupervised model-based validation of peptide identifications in mass spectrometry-based proteomics.

Choi H, Nesvizhskii AI.

J Proteome Res. 2008 Jan;7(1):254-65. Epub 2007 Dec 27.

PMID:
18159924
5.

Accurate assignment of significance to neuropeptide identifications using Monte Carlo k-permuted decoy databases.

Akhtar MN, Southey BR, Andrén PE, Sweedler JV, Rodriguez-Zas SL.

PLoS One. 2014 Oct 17;9(10):e111112. doi: 10.1371/journal.pone.0111112. eCollection 2014.

6.

Evaluation of database search programs for accurate detection of neuropeptides in tandem mass spectrometry experiments.

Akhtar MN, Southey BR, Andrén PE, Sweedler JV, Rodriguez-Zas SL.

J Proteome Res. 2012 Dec 7;11(12):6044-55. doi: 10.1021/pr3007123. Epub 2012 Nov 6.

7.

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

Kwon T, Choi H, Vogel C, Nesvizhskii AI, Marcotte EM.

J Proteome Res. 2011 Jul 1;10(7):2949-58. doi: 10.1021/pr2002116. Epub 2011 Apr 29.

8.

OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction.

Wang Y, Yang F, Wu P, Bu D, Sun S.

BMC Bioinformatics. 2015 Apr 2;16:110. doi: 10.1186/s12859-015-0540-1.

9.
10.

Crescendo: A Protein Sequence Database Search Engine for Tandem Mass Spectra.

Wang J, Zhang Y, Yu Y.

J Am Soc Mass Spectrom. 2015 Jul;26(7):1077-84. doi: 10.1007/s13361-015-1120-3. Epub 2015 Apr 21.

PMID:
25895889
11.

Enhanced peptide quantification using spectral count clustering and cluster abundance.

Lee S, Kwon MS, Lee HJ, Paik YK, Tang H, Lee JK, Park T.

BMC Bioinformatics. 2011 Oct 28;12:423. doi: 10.1186/1471-2105-12-423.

12.

Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.

Keich U, Kertesz-Farkas A, Noble WS.

J Proteome Res. 2015 Aug 7;14(8):3148-61. doi: 10.1021/acs.jproteome.5b00081. Epub 2015 Jul 27.

13.

Improvements to the percolator algorithm for Peptide identification from shotgun proteomics data sets.

Spivak M, Weston J, Bottou L, Käll L, Noble WS.

J Proteome Res. 2009 Jul;8(7):3737-45. doi: 10.1021/pr801109k.

14.
15.

Identification of best indicators of peptide-spectrum match using a permutation resampling approach.

Akhtar MN, Southey BR, Andrén PE, Sweedler JV, Rodriguez-Zas SL.

J Bioinform Comput Biol. 2014 Oct;12(5):1440001. doi: 10.1142/S0219720014400010.

16.

Context-sensitive markov models for peptide scoring and identification from tandem mass spectrometry.

Grover H, Wallstrom G, Wu CC, Gopalakrishnan V.

OMICS. 2013 Feb;17(2):94-105. doi: 10.1089/omi.2012.0073. Epub 2013 Jan 5.

17.

SQID: an intensity-incorporated protein identification algorithm for tandem mass spectrometry.

Li W, Ji L, Goya J, Tan G, Wysocki VH.

J Proteome Res. 2011 Apr 1;10(4):1593-602. doi: 10.1021/pr100959y. Epub 2011 Feb 23.

18.
19.

Two-dimensional target decoy strategy for shotgun proteomics.

Bern MW, Kil YJ.

J Proteome Res. 2011 Dec 2;10(12):5296-301. doi: 10.1021/pr200780j. Epub 2011 Nov 7.

20.

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