255 related articles for article (PubMed ID: 34312990)
1. DDASSQ: An open-source, multiple peptide sequencing strategy for label free quantification based on an OpenMS pipeline in the KNIME analytics platform.
Svecla M; Garrone G; Faré F; Aletti G; Norata GD; Beretta G
Proteomics; 2021 Aug; 21(16):e2000319. PubMed ID: 34312990
[TBL] [Abstract][Full Text] [Related]
2. In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.
Audain E; Uszkoreit J; Sachsenberg T; Pfeuffer J; Liang X; Hermjakob H; Sanchez A; Eisenacher M; Reinert K; Tabb DL; Kohlbacher O; Perez-Riverol Y
J Proteomics; 2017 Jan; 150():170-182. PubMed ID: 27498275
[TBL] [Abstract][Full Text] [Related]
3. An automated pipeline for high-throughput label-free quantitative proteomics.
Weisser H; Nahnsen S; Grossmann J; Nilse L; Quandt A; Brauer H; Sturm M; Kenar E; Kohlbacher O; Aebersold R; Malmström L
J Proteome Res; 2013 Apr; 12(4):1628-44. PubMed ID: 23391308
[TBL] [Abstract][Full Text] [Related]
4. Comparative database search engine analysis on massive tandem mass spectra of pork-based food products for halal proteomics.
Amir SH; Yuswan MH; Aizat WM; Mansor MK; Desa MNM; Yusof YA; Song LK; Mustafa S
J Proteomics; 2021 Jun; 241():104240. PubMed ID: 33894373
[TBL] [Abstract][Full Text] [Related]
5. Constructing a Tandem Mass Spectral Library for Forensic Ricin Identification.
O'Bryon I; Tucker AE; Kaiser BLD; Wahl KL; Merkley ED
J Proteome Res; 2019 Nov; 18(11):3926-3935. PubMed ID: 31566388
[TBL] [Abstract][Full Text] [Related]
6. An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics.
Wu C; Monroe ME; Xu Z; Slysz GW; Payne SH; Rodland KD; Liu T; Smith RD
J Am Soc Mass Spectrom; 2015 Dec; 26(12):2002-8. PubMed ID: 26015166
[TBL] [Abstract][Full Text] [Related]
7. MaxQuant Software for Ion Mobility Enhanced Shotgun Proteomics.
Prianichnikov N; Koch H; Koch S; Lubeck M; Heilig R; Brehmer S; Fischer R; Cox J
Mol Cell Proteomics; 2020 Jun; 19(6):1058-1069. PubMed ID: 32156793
[TBL] [Abstract][Full Text] [Related]
8. Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.
Perez-Riverol Y; Wang R; Hermjakob H; Müller M; Vesada V; Vizcaíno JA
Biochim Biophys Acta; 2014 Jan; 1844(1 Pt A):63-76. PubMed ID: 23467006
[TBL] [Abstract][Full Text] [Related]
9. Targeted Feature Detection for Data-Dependent Shotgun Proteomics.
Weisser H; Choudhary JS
J Proteome Res; 2017 Aug; 16(8):2964-2974. PubMed ID: 28673088
[TBL] [Abstract][Full Text] [Related]
10. Enhanced peptide quantification using spectral count clustering and cluster abundance.
Lee S; Kwon MS; Lee HJ; Paik YK; Tang H; Lee JK; Park T
BMC Bioinformatics; 2011 Oct; 12():423. PubMed ID: 22034872
[TBL] [Abstract][Full Text] [Related]
11. Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.
Ramus C; Hovasse A; Marcellin M; Hesse AM; Mouton-Barbosa E; Bouyssié D; Vaca S; Carapito C; Chaoui K; Bruley C; Garin J; Cianférani S; Ferro M; Van Dorssaeler A; Burlet-Schiltz O; Schaeffer C; Couté Y; Gonzalez de Peredo A
J Proteomics; 2016 Jan; 132():51-62. PubMed ID: 26585461
[TBL] [Abstract][Full Text] [Related]
12. The APEX Quantitative Proteomics Tool: generating protein quantitation estimates from LC-MS/MS proteomics results.
Braisted JC; Kuntumalla S; Vogel C; Marcotte EM; Rodrigues AR; Wang R; Huang ST; Ferlanti ES; Saeed AI; Fleischmann RD; Peterson SN; Pieper R
BMC Bioinformatics; 2008 Dec; 9():529. PubMed ID: 19068132
[TBL] [Abstract][Full Text] [Related]
13. Protein Inference Using PIA Workflows and PSI Standard File Formats.
Uszkoreit J; Perez-Riverol Y; Eggers B; Marcus K; Eisenacher M
J Proteome Res; 2019 Feb; 18(2):741-747. PubMed ID: 30474983
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates.
Shteynberg D; Deutsch EW; Lam H; Eng JK; Sun Z; Tasman N; Mendoza L; Moritz RL; Aebersold R; Nesvizhskii AI
Mol Cell Proteomics; 2011 Dec; 10(12):M111.007690. PubMed ID: 21876204
[TBL] [Abstract][Full Text] [Related]
16. Evaluating de novo sequencing in proteomics: already an accurate alternative to database-driven peptide identification?
Muth T; Renard BY
Brief Bioinform; 2018 Sep; 19(5):954-970. PubMed ID: 28369237
[TBL] [Abstract][Full Text] [Related]
17. Comparative evaluation of label-free quantification strategies.
Zhao L; Cong X; Zhai L; Hu H; Xu JY; Zhao W; Zhu M; Tan M; Ye BC
J Proteomics; 2020 Mar; 215():103669. PubMed ID: 31987925
[TBL] [Abstract][Full Text] [Related]
18. 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
Proteomics; 2012 Dec; 12(23-24):3475-84. PubMed ID: 23081734
[TBL] [Abstract][Full Text] [Related]
19. OpenMS and TOPP: open source software for LC-MS data analysis.
Reinert K; Kohlbacher O
Methods Mol Biol; 2010; 604():201-11. PubMed ID: 20013373
[TBL] [Abstract][Full Text] [Related]
20. Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry.
Aiche S; Sachsenberg T; Kenar E; Walzer M; Wiswedel B; Kristl T; Boyles M; Duschl A; Huber CG; Berthold MR; Reinert K; Kohlbacher O
Proteomics; 2015 Apr; 15(8):1443-7. PubMed ID: 25604327
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]