253 related articles for article (PubMed ID: 33813065)
1. IonQuant Enables Accurate and Sensitive Label-Free Quantification With FDR-Controlled Match-Between-Runs.
Yu F; Haynes SE; Nesvizhskii AI
Mol Cell Proteomics; 2021; 20():100077. PubMed ID: 33813065
[TBL] [Abstract][Full Text] [Related]
2. Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant.
Yu F; Haynes SE; Teo GC; Avtonomov DM; Polasky DA; Nesvizhskii AI
Mol Cell Proteomics; 2020 Sep; 19(9):1575-1585. PubMed ID: 32616513
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model.
Lim MY; Paulo JA; Gygi SP
J Proteome Res; 2019 Nov; 18(11):4020-4026. PubMed ID: 31547658
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.
Meier F; Brunner AD; Koch S; Koch H; Lubeck M; Krause M; Goedecke N; Decker J; Kosinski T; Park MA; Bache N; Hoerning O; Cox J; Räther O; Mann M
Mol Cell Proteomics; 2018 Dec; 17(12):2534-2545. PubMed ID: 30385480
[TBL] [Abstract][Full Text] [Related]
8. ProteinInferencer: Confident protein identification and multiple experiment comparison for large scale proteomics projects.
Zhang Y; Xu T; Shan B; Hart J; Aslanian A; Han X; Zong N; Li H; Choi H; Wang D; Acharya L; Du L; Vogt PK; Ping P; Yates JR
J Proteomics; 2015 Nov; 129():25-32. PubMed ID: 26196237
[TBL] [Abstract][Full Text] [Related]
9. Validation of MS/MS Identifications and Label-Free Quantification Using Proline.
Dupierris V; Hesse AM; Menetrey JP; Bouyssié D; Burger T; Couté Y; Bruley C
Methods Mol Biol; 2023; 2426():67-89. PubMed ID: 36308685
[TBL] [Abstract][Full Text] [Related]
10. A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry.
Aoshima K; Takahashi K; Ikawa M; Kimura T; Fukuda M; Tanaka S; Parry HE; Fujita Y; Yoshizawa AC; Utsunomiya S; Kajihara S; Tanaka K; Oda Y
BMC Bioinformatics; 2014 Nov; 15(1):376. PubMed ID: 25420746
[TBL] [Abstract][Full Text] [Related]
11. Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data.
Tu C; Sheng Q; Li J; Ma D; Shen X; Wang X; Shyr Y; Yi Z; Qu J
J Proteome Res; 2015 Nov; 14(11):4662-73. PubMed ID: 26390080
[TBL] [Abstract][Full Text] [Related]
12. MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides.
Wichmann C; Meier F; Virreira Winter S; Brunner AD; Cox J; Mann M
Mol Cell Proteomics; 2019 May; 18(5):982-994. PubMed ID: 30755466
[TBL] [Abstract][Full Text] [Related]
13. Reanalysis of ProteomicsDB Using an Accurate, Sensitive, and Scalable False Discovery Rate Estimation Approach for Protein Groups.
The M; Samaras P; Kuster B; Wilhelm M
Mol Cell Proteomics; 2022 Dec; 21(12):100437. PubMed ID: 36328188
[TBL] [Abstract][Full Text] [Related]
14. ProtyQuant: Comparing label-free shotgun proteomics datasets using accumulated peptide probabilities.
Winkler R
J Proteomics; 2021 Jan; 230():103985. PubMed ID: 32956841
[TBL] [Abstract][Full Text] [Related]
15. A proteomics search algorithm specifically designed for high-resolution tandem mass spectra.
Wenger CD; Coon JJ
J Proteome Res; 2013 Mar; 12(3):1377-86. PubMed ID: 23323968
[TBL] [Abstract][Full Text] [Related]
16. Assessment of label-free quantification and missing value imputation for proteomics in non-human primates.
Hamid Z; Zimmerman KD; Guillen-Ahlers H; Li C; Nathanielsz P; Cox LA; Olivier M
BMC Genomics; 2022 Jul; 23(1):496. PubMed ID: 35804317
[TBL] [Abstract][Full Text] [Related]
17. Combining De Novo Peptide Sequencing Algorithms, A Synergistic Approach to Boost Both Identifications and Confidence in Bottom-up Proteomics.
Blank-Landeshammer B; Kollipara L; Biß K; Pfenninger M; Malchow S; Shuvaev K; Zahedi RP; Sickmann A
J Proteome Res; 2017 Sep; 16(9):3209-3218. PubMed ID: 28741358
[TBL] [Abstract][Full Text] [Related]
18. An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.
Shen X; Shen S; Li J; Hu Q; Nie L; Tu C; Wang X; Orsburn B; Wang J; Qu J
J Proteome Res; 2017 Jul; 16(7):2445-2456. PubMed ID: 28412812
[TBL] [Abstract][Full Text] [Related]
19. Tandem Mass Spectrum Identification via Cascaded Search.
Kertesz-Farkas A; Keich U; Noble WS
J Proteome Res; 2015 Aug; 14(8):3027-38. PubMed ID: 26084232
[TBL] [Abstract][Full Text] [Related]
20. DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis.
Zhu Y; Orre LM; Zhou Tran Y; Mermelekas G; Johansson HJ; Malyutina A; Anders S; Lehtiö J
Mol Cell Proteomics; 2020 Jun; 19(6):1047-1057. PubMed ID: 32205417
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
