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Items: 1 to 20 of 114

1.

Evaluation of signal peptide prediction algorithms for identification of mycobacterial signal peptides using sequence data from proteomic methods.

Leversen NA, de Souza GA, Målen H, Prasad S, Jonassen I, Wiker HG.

Microbiology. 2009 Jul;155(Pt 7):2375-83. doi: 10.1099/mic.0.025270-0. Epub 2009 Apr 23.

2.

Identification of putative exported/secreted proteins in prokaryotic proteomes.

Saleh MT, Fillon M, Brennan PJ, Belisle JT.

Gene. 2001 May 16;269(1-2):195-204.

PMID:
11376951
3.

Signal peptide prediction based on analysis of experimentally verified cleavage sites.

Zhang Z, Henzel WJ.

Protein Sci. 2004 Oct;13(10):2819-24. Epub 2004 Aug 31.

4.

Prediction of lipoprotein signal peptides in Gram-positive bacteria with a Hidden Markov Model.

Bagos PG, Tsirigos KD, Liakopoulos TD, Hamodrakas SJ.

J Proteome Res. 2008 Dec;7(12):5082-93. doi: 10.1021/pr800162c.

PMID:
19367716
5.
6.

Improved prediction of signal peptides: SignalP 3.0.

Bendtsen JD, Nielsen H, von Heijne G, Brunak S.

J Mol Biol. 2004 Jul 16;340(4):783-95.

PMID:
15223320
7.

Prediction of signal peptides and signal anchors by a hidden Markov model.

Nielsen H, Krogh A.

Proc Int Conf Intell Syst Mol Biol. 1998;6:122-30.

PMID:
9783217
8.

Machine learning approaches for the prediction of signal peptides and other protein sorting signals.

Nielsen H, Brunak S, von Heijne G.

Protein Eng. 1999 Jan;12(1):3-9. Review.

PMID:
10065704
9.

Combined prediction of Tat and Sec signal peptides with hidden Markov models.

Bagos PG, Nikolaou EP, Liakopoulos TD, Tsirigos KD.

Bioinformatics. 2010 Nov 15;26(22):2811-7. doi: 10.1093/bioinformatics/btq530. Epub 2010 Sep 16.

PMID:
20847219
10.

Identification of new protein coding sequences and signal peptidase cleavage sites of Helicobacter pylori strain 26695 by proteogenomics.

Müller SA, Findeiß S, Pernitzsch SR, Wissenbach DK, Stadler PF, Hofacker IL, von Bergen M, Kalkhof S.

J Proteomics. 2013 Jun 28;86:27-42. doi: 10.1016/j.jprot.2013.04.036. Epub 2013 May 9.

PMID:
23665149
11.

Prediction of lipoprotein signal peptides in Gram-negative bacteria.

Juncker AS, Willenbrock H, Von Heijne G, Brunak S, Nielsen H, Krogh A.

Protein Sci. 2003 Aug;12(8):1652-62.

12.

Combined prediction of transmembrane topology and signal peptide of beta-barrel proteins: using a hidden Markov model and genetic algorithms.

Zou L, Wang Z, Wang Y, Hu F.

Comput Biol Med. 2010 Jul;40(7):621-8. doi: 10.1016/j.compbiomed.2010.04.006. Epub 2010 May 21.

PMID:
20488436
13.
14.

A proteomic view on genome-based signal peptide predictions.

Antelmann H, Tjalsma H, Voigt B, Ohlmeier S, Bron S, van Dijl JM, Hecker M.

Genome Res. 2001 Sep;11(9):1484-502.

15.

Computational differentiation of N-terminal signal peptides and transmembrane helices.

Yuan Z, Davis MJ, Zhang F, Teasdale RD.

Biochem Biophys Res Commun. 2003 Dec 26;312(4):1278-83.

PMID:
14652012
17.

Identification of novel peptide hormones in the human proteome by hidden Markov model screening.

Mirabeau O, Perlas E, Severini C, Audero E, Gascuel O, Possenti R, Birney E, Rosenthal N, Gross C.

Genome Res. 2007 Mar;17(3):320-7. Epub 2007 Feb 6.

18.

Prediction of signal peptides in archaea.

Bagos PG, Tsirigos KD, Plessas SK, Liakopoulos TD, Hamodrakas SJ.

Protein Eng Des Sel. 2009 Jan;22(1):27-35. doi: 10.1093/protein/gzn064. Epub 2008 Nov 6.

PMID:
18988691
19.

A comprehensive assessment of N-terminal signal peptides prediction methods.

Choo KH, Tan TW, Ranganathan S.

BMC Bioinformatics. 2009 Dec 3;10 Suppl 15:S2. doi: 10.1186/1471-2105-10-S15-S2.

20.

A database for Mycobacterium secretome analysis: 'MycoSec' to accelerate global health research.

Roy A, Bhattacharya S, Bothra AK, Sen A.

OMICS. 2013 Oct;17(10):502-9. doi: 10.1089/omi.2013.0015. Epub 2013 Aug 16.

PMID:
23952586

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