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Items: 1 to 20 of 26

1.

Treatment of missing values for multivariate statistical analysis of gel-based proteomics data.

Pedreschi R, Hertog ML, Carpentier SC, Lammertyn J, Robben J, Noben JP, Panis B, Swennen R, Nicolaï BM.

Proteomics. 2008 Apr;8(7):1371-83. doi: 10.1002/pmic.200700975.

PMID:
18383008
2.

Missing values in gel-based proteomics.

Albrecht D, Kniemeyer O, Brakhage AA, Guthke R.

Proteomics. 2010 Mar;10(6):1202-11. doi: 10.1002/pmic.200800576. Review.

PMID:
20077407
3.

Multivariate approaches in plant science.

Gottlieb DM, Schultz J, Bruun SW, Jacobsen S, Søndergaard I.

Phytochemistry. 2004 Jun;65(11):1531-48. Review.

PMID:
15276450
4.

2D-PAGE maps analysis.

Marengo E, Robotti E, Bobba M.

Methods Mol Biol. 2008;428:291-325. Review.

PMID:
18287780
5.

Finding the significant markers: statistical analysis of proteomic data.

Carpentier SC, Panis B, Swennen R, Lammertyn J.

Methods Mol Biol. 2008;428:327-47. Review.

PMID:
18287781
6.

Statistics for proteomics: a review of tools for analyzing experimental data.

Urfer W, Grzegorczyk M, Jung K.

Proteomics. 2006 Sep;6 Suppl 2:48-55. Review.

PMID:
17031797
7.

Multivariate modeling of missing data within and across assessment waves.

Figueredo AJ, McKnight PE, McKnight KM, Sidani S.

Addiction. 2000 Nov;95 Suppl 3:S361-80. Review.

PMID:
11132363
8.

Effects of post-electrophoretic analysis on variance in gel-based proteomics.

Wheelock AM, Goto S.

Expert Rev Proteomics. 2006 Feb;3(1):129-42. Review.

PMID:
16445357
9.

Difference gel electrophoresis.

Timms JF, Cramer R.

Proteomics. 2008 Dec;8(23-24):4886-97. doi: 10.1002/pmic.200800298. Review.

PMID:
19003860
10.

Difference gel electrophoresis.

Minden JS, Dowd SR, Meyer HE, Stühler K.

Electrophoresis. 2009 Jun;30 Suppl 1:S156-61. doi: 10.1002/elps.200900098. Review.

PMID:
19517495
11.

Membrane proteins and proteomics: love is possible, but so difficult.

Rabilloud T.

Electrophoresis. 2009 Jun;30 Suppl 1:S174-80. doi: 10.1002/elps.200900050. Review.

12.

Modern robust statistical methods: an easy way to maximize the accuracy and power of your research.

Erceg-Hurn DM, Mirosevich VM.

Am Psychol. 2008 Oct;63(7):591-601. doi: 10.1037/0003-066X.63.7.591. Review.

PMID:
18855490
13.
14.

Gel-based proteomics of Gram-positive bacteria: a powerful tool to address physiological questions.

Hecker M, Antelmann H, Büttner K, Bernhardt J.

Proteomics. 2008 Dec;8(23-24):4958-75. doi: 10.1002/pmic.200800278. Review.

PMID:
19003856
15.

Proteomics in the study of the molecular taxonomy and epidemiology of bacterial pathogens.

Cash P.

Electrophoresis. 2009 Jun;30 Suppl 1:S133-41. doi: 10.1002/elps.200900059. Review.

PMID:
19517493
16.

Back to the basics: Maximizing the information obtained by quantitative two dimensional gel electrophoresis analyses by an appropriate experimental design and statistical analyses.

Valledor L, Jorrín J.

J Proteomics. 2011 Jan 1;74(1):1-18. doi: 10.1016/j.jprot.2010.07.007. Epub 2010 Jul 23. Review.

PMID:
20656082
17.

Fully denaturing two-dimensional electrophoresis of membrane proteins: a critical update.

Rabilloud T, Chevallet M, Luche S, Lelong C.

Proteomics. 2008 Oct;8(19):3965-73. doi: 10.1002/pmic.200800043. Review.

18.

Chemometrics in metabonomics.

Trygg J, Holmes E, Lundstedt T.

J Proteome Res. 2007 Feb;6(2):469-79. Review.

PMID:
17269704
19.

Why, when, and how biochemists should use least squares.

Johnson ML.

Anal Biochem. 1992 Nov 1;206(2):215-25. Review.

PMID:
1443589
20.

Data analysis techniques in phosphoproteomics.

Meyer-Baese A, Wildberger J, Meyer-Baese U, Nilsson CL.

Electrophoresis. 2014 Dec;35(24):3452-62. doi: 10.1002/elps.201400219. Epub 2014 Nov 25. Review.

PMID:
25311575

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