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Items: 1 to 20 of 123

1.

A cross-validation scheme for machine learning algorithms in shotgun proteomics.

Granholm V, Noble WS, Käll L.

BMC Bioinformatics. 2012;13 Suppl 16:S3. doi: 10.1186/1471-2105-13-S16-S3. Epub 2012 Nov 5.

2.

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
3.

Transferred subgroup false discovery rate for rare post-translational modifications detected by mass spectrometry.

Fu Y, Qian X.

Mol Cell Proteomics. 2014 May;13(5):1359-68. doi: 10.1074/mcp.O113.030189. Epub 2013 Nov 7.

4.

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.

5.

MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm.

Cerqueira FR, Ricardo AM, de Paiva Oliveira A, Graber A, Baumgartner C.

BMC Bioinformatics. 2016 Dec 15;17(Suppl 18):472. doi: 10.1186/s12859-016-1341-x.

6.

Analysis of the resolution limitations of peptide identification algorithms.

Colaert N, Degroeve S, Helsens K, Martens L.

J Proteome Res. 2011 Dec 2;10(12):5555-61. doi: 10.1021/pr200913a. Epub 2011 Oct 26.

PMID:
21995378
7.

Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides.

Heller M, Ye M, Michel PE, Morier P, Stalder D, Jünger MA, Aebersold R, Reymond F, Rossier JS.

J Proteome Res. 2005 Nov-Dec;4(6):2273-82.

PMID:
16335976
8.

MUMAL: multivariate analysis in shotgun proteomics using machine learning techniques.

Cerqueira FR, Ferreira RS, Oliveira AP, Gomes AP, Ramos HJ, Graber A, Baumgartner C.

BMC Genomics. 2012;13 Suppl 5:S4. doi: 10.1186/1471-2164-13-S5-S4. Epub 2012 Oct 19.

9.

Improved machine learning method for analysis of gas phase chemistry of peptides.

Gehrke A, Sun S, Kurgan L, Ahn N, Resing K, Kafadar K, Cios K.

BMC Bioinformatics. 2008 Dec 3;9:515. doi: 10.1186/1471-2105-9-515.

10.

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.

11.

A decoy-free approach to the identification of peptides.

Gonnelli G, Stock M, Verwaeren J, Maddelein D, De Baets B, Martens L, Degroeve S.

J Proteome Res. 2015 Apr 3;14(4):1792-8. doi: 10.1021/pr501164r. Epub 2015 Mar 6.

PMID:
25714903
12.

False discovery rates of protein identifications: a strike against the two-peptide rule.

Gupta N, Pevzner PA.

J Proteome Res. 2009 Sep;8(9):4173-81. doi: 10.1021/pr9004794.

13.
14.

MUDE: a new approach for optimizing sensitivity in the target-decoy search strategy for large-scale peptide/protein identification.

Cerqueira FR, Graber A, Schwikowski B, Baumgartner C.

J Proteome Res. 2010 May 7;9(5):2265-77. doi: 10.1021/pr901023v.

PMID:
20199108
15.

Artificial decoy spectral libraries for false discovery rate estimation in spectral library searching in proteomics.

Lam H, Deutsch EW, Aebersold R.

J Proteome Res. 2010 Jan;9(1):605-10. doi: 10.1021/pr900947u.

PMID:
19916561
16.

Intensity-based protein identification by machine learning from a library of tandem mass spectra.

Elias JE, Gibbons FD, King OD, Roth FP, Gygi SP.

Nat Biotechnol. 2004 Feb;22(2):214-9. Epub 2004 Jan 18.

PMID:
14730315
17.

Effective Leveraging of Targeted Search Spaces for Improving Peptide Identification in Tandem Mass Spectrometry Based Proteomics.

Shanmugam AK, Nesvizhskii AI.

J Proteome Res. 2015 Dec 4;14(12):5169-78. doi: 10.1021/acs.jproteome.5b00504. Epub 2015 Nov 24.

18.
19.

Peak intensity prediction in MALDI-TOF mass spectrometry: a machine learning study to support quantitative proteomics.

Timm W, Scherbart A, Böcker S, Kohlbacher O, Nattkemper TW.

BMC Bioinformatics. 2008 Oct 20;9:443. doi: 10.1186/1471-2105-9-443.

20.

Current algorithmic solutions for peptide-based proteomics data generation and identification.

Hoopmann MR, Moritz RL.

Curr Opin Biotechnol. 2013 Feb;24(1):31-8. doi: 10.1016/j.copbio.2012.10.013. Epub 2012 Nov 8. Review.

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