Zhang J - Search Results

1

Improving the sensitivity of MASCOT search results validation by combining new features with Bayesian nonparametric model.

Ma J, Zhang J, Wu S, Li D, Zhu Y, He F. Ma J, et al. Among authors: zhang j. Proteomics. 2010 Dec;10(23):4293-300. doi: 10.1002/pmic.200900668. Proteomics. 2010. PMID: 21086516

2

Phosphoproteome analysis of the human Chang liver cells using SCX and a complementary mass spectrometric strategy.

Sui S, Wang J, Yang B, Song L, Zhang J, Chen M, Liu J, Lu Z, Cai Y, Chen S, Bi W, Zhu Y, He F, Qian X. Sui S, et al. Among authors: zhang j. Proteomics. 2008 May;8(10):2024-34. doi: 10.1002/pmic.200700896. Proteomics. 2008. PMID: 18491316

3

Bayesian nonparametric model for the validation of peptide identification in shotgun proteomics.

Zhang J, Ma J, Dou L, Wu S, Qian X, Xie H, Zhu Y, He F. Zhang J, et al. Mol Cell Proteomics. 2009 Mar;8(3):547-57. doi: 10.1074/mcp.M700558-MCP200. Epub 2008 Nov 12. Mol Cell Proteomics. 2009. PMID: 19005226 Free PMC article.

4

PepDistiller: A quality control tool to improve the sensitivity and accuracy of peptide identifications in shotgun proteomics.

Li N, Wu S, Zhang C, Chang C, Zhang J, Ma J, Li L, Qian X, Xu P, Zhu Y, He F. Li N, et al. Among authors: zhang c, zhang j. Proteomics. 2012 Jun;12(11):1720-5. doi: 10.1002/pmic.201100167. Proteomics. 2012. PMID: 22623377

5

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

Zhang W, Zhang J, Xu C, Li N, Liu H, Ma J, Zhu Y, Xie H. Zhang W, et al. Among authors: zhang j. Proteomics. 2012 Dec;12(23-24):3475-84. doi: 10.1002/pmic.201200017. Proteomics. 2012. PMID: 23081734

6

A new strategy to filter out false positive identifications of peptides in SEQUEST database search results.

Zhang J, Li J, Xie H, Zhu Y, He F. Zhang J, et al. Proteomics. 2007 Nov;7(22):4036-44. doi: 10.1002/pmic.200600929. Proteomics. 2007. PMID: 17952874

7

Mass measurement errors of Fourier-transform mass spectrometry (FTMS): distribution, recalibration, and application.

Zhang J, Ma J, Dou L, Wu S, Qian X, Xie H, Zhu Y, He F. Zhang J, et al. J Proteome Res. 2009 Feb;8(2):849-59. doi: 10.1021/pr8005588. J Proteome Res. 2009. PMID: 19102693

8

A systematic N-terminal peptide quantitative labeling strategy for differential proteomic analysis.

Liu X, Zhang J, Zheng Z, Yang X, Jia W, Li L, Gong Y, Cai Y, Zhu Y, He F, Ying W, Qian X. Liu X, et al. Among authors: zhang j. Proteomics Clin Appl. 2010 Jul;4(6-7):633-43. doi: 10.1002/prca.200900065. Epub 2010 Mar 9. Proteomics Clin Appl. 2010. PMID: 21137082

9

Proteome-wide prediction of self-interacting proteins based on multiple properties.

Liu Z, Guo F, Zhang J, Wang J, Lu L, Li D, He F. Liu Z, et al. Among authors: zhang j. Mol Cell Proteomics. 2013 Jun;12(6):1689-700. doi: 10.1074/mcp.M112.021790. Epub 2013 Feb 18. Mol Cell Proteomics. 2013. PMID: 23422585 Free PMC article.

10

SILVER: an efficient tool for stable isotope labeling LC-MS data quantitative analysis with quality control methods.

Chang C, Zhang J, Han M, Ma J, Zhang W, Wu S, Liu K, Xie H, He F, Zhu Y. Chang C, et al. Among authors: zhang w, zhang j. Bioinformatics. 2014 Feb 15;30(4):586-7. doi: 10.1093/bioinformatics/btt726. Epub 2013 Dec 15. Bioinformatics. 2014. PMID: 24344194

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