176 related articles for article (PubMed ID: 24928210)
1. Detecting differential protein expression in large-scale population proteomics.
Ryu SY; Qian WJ; Camp DG; Smith RD; Tompkins RG; Davis RW; Xiao W
Bioinformatics; 2014 Oct; 30(19):2741-6. PubMed ID: 24928210
[TBL] [Abstract][Full Text] [Related]
2. Large-scale multiplexed quantitative discovery proteomics enabled by the use of an (18)O-labeled "universal" reference sample.
Qian WJ; Liu T; Petyuk VA; Gritsenko MA; Petritis BO; Polpitiya AD; Kaushal A; Xiao W; Finnerty CC; Jeschke MG; Jaitly N; Monroe ME; Moore RJ; Moldawer LL; Davis RW; Tompkins RG; Herndon DN; Camp DG; Smith RD;
J Proteome Res; 2009 Jan; 8(1):290-9. PubMed ID: 19053531
[TBL] [Abstract][Full Text] [Related]
3. EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh HW; Swa HL; Fermin D; Ler SG; Gunaratne J; Choi H
Proteomics; 2015 Aug; 15(15):2580-91. PubMed ID: 25913743
[TBL] [Abstract][Full Text] [Related]
4. Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells.
Bouyssié D; Gonzalez de Peredo A; Mouton E; Albigot R; Roussel L; Ortega N; Cayrol C; Burlet-Schiltz O; Girard JP; Monsarrat B
Mol Cell Proteomics; 2007 Sep; 6(9):1621-37. PubMed ID: 17533220
[TBL] [Abstract][Full Text] [Related]
5. MS-EmpiRe Utilizes Peptide-level Noise Distributions for Ultra-sensitive Detection of Differentially Expressed Proteins.
Ammar C; Gruber M; Csaba G; Zimmer R
Mol Cell Proteomics; 2019 Sep; 18(9):1880-1892. PubMed ID: 31235637
[TBL] [Abstract][Full Text] [Related]
6. Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments.
Albaum SP; Neuweger H; Fränzel B; Lange S; Mertens D; Trötschel C; Wolters D; Kalinowski J; Nattkemper TW; Goesmann A
Bioinformatics; 2009 Dec; 25(23):3128-34. PubMed ID: 19808875
[TBL] [Abstract][Full Text] [Related]
7. Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.
Goeminne LJE; Gevaert K; Clement L
J Proteomics; 2018 Jan; 171():23-36. PubMed ID: 28391044
[TBL] [Abstract][Full Text] [Related]
8. Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics.
Brusniak MY; Bodenmiller B; Campbell D; Cooke K; Eddes J; Garbutt A; Lau H; Letarte S; Mueller LN; Sharma V; Vitek O; Zhang N; Aebersold R; Watts JD
BMC Bioinformatics; 2008 Dec; 9():542. PubMed ID: 19087345
[TBL] [Abstract][Full Text] [Related]
9. Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition.
Karpievitch YV; Taverner T; Adkins JN; Callister SJ; Anderson GA; Smith RD; Dabney AR
Bioinformatics; 2009 Oct; 25(19):2573-80. PubMed ID: 19602524
[TBL] [Abstract][Full Text] [Related]
10. Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics.
Langley SR; Mayr M
J Proteomics; 2015 Nov; 129():83-92. PubMed ID: 26193490
[TBL] [Abstract][Full Text] [Related]
11. A reference peptide database for proteome quantification based on experimental mass spectrum response curves.
Liu W; Wei L; Sun J; Feng J; Guo G; Liang L; Fu T; Liu M; Li K; Huang Y; Zhu W; Zhen B; Wang Y; Ding C; Qin J
Bioinformatics; 2018 Aug; 34(16):2766-2772. PubMed ID: 29617941
[TBL] [Abstract][Full Text] [Related]
12. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.
Lin L; Zheng J; Yu Q; Chen W; Xing J; Chen C; Tian R
J Proteomics; 2018 Mar; 174():9-16. PubMed ID: 29278786
[TBL] [Abstract][Full Text] [Related]
13. Bioinformatics challenges in mass spectrometry-driven proteomics.
Martens L
Methods Mol Biol; 2011; 753():359-71. PubMed ID: 21604135
[TBL] [Abstract][Full Text] [Related]
14. Analysis of mass spectrometry data in proteomics.
Matthiesen R; Jensen ON
Methods Mol Biol; 2008; 453():105-22. PubMed ID: 18712299
[TBL] [Abstract][Full Text] [Related]
15. A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification.
Tu C; Shen S; Sheng Q; Shyr Y; Qu J
J Proteomics; 2017 Jan; 152():276-282. PubMed ID: 27903464
[TBL] [Abstract][Full Text] [Related]
16. Peptide sequence confidence in accurate mass and time analysis and its use in complex proteomics experiments.
May D; Liu Y; Law W; Fitzgibbon M; Wang H; Hanash S; McIntosh M
J Proteome Res; 2008 Dec; 7(12):5148-56. PubMed ID: 19367719
[TBL] [Abstract][Full Text] [Related]
17. Including shared peptides for estimating protein abundances: a significant improvement for quantitative proteomics.
Blein-Nicolas M; Xu H; de Vienne D; Giraud C; Huet S; Zivy M
Proteomics; 2012 Sep; 12(18):2797-801. PubMed ID: 22833229
[TBL] [Abstract][Full Text] [Related]
18. Mining gene functional networks to improve mass-spectrometry-based protein identification.
Ramakrishnan SR; Vogel C; Kwon T; Penalva LO; Marcotte EM; Miranker DP
Bioinformatics; 2009 Nov; 25(22):2955-61. PubMed ID: 19633097
[TBL] [Abstract][Full Text] [Related]
19. What is targeted proteomics? A concise revision of targeted acquisition and targeted data analysis in mass spectrometry.
Borràs E; Sabidó E
Proteomics; 2017 Sep; 17(17-18):. PubMed ID: 28719092
[TBL] [Abstract][Full Text] [Related]
20. KYSS: mass spectrometry data quality assessment for protein analysis and large-scale proteomics.
Such-Sanmartín G; Sidoli S; Ventura-Espejo E; Jensen ON
Biochem Biophys Res Commun; 2014 Mar; 445(4):702-7. PubMed ID: 24480439
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]