143 related articles for article (PubMed ID: 38393017)
1. metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics.
Habra H; Meijer JL; Shen T; Fiehn O; Gaul DA; Fernández FM; Rempfert KR; Metz TO; Peterson KE; Evans CR; Karnovsky A
Metabolites; 2024 Feb; 14(2):. PubMed ID: 38393017
[TBL] [Abstract][Full Text] [Related]
2.
Habra H; Kachman M; Bullock K; Clish C; Evans CR; Karnovsky A
Anal Chem; 2021 Mar; 93(12):5028-5036. PubMed ID: 33724799
[TBL] [Abstract][Full Text] [Related]
3. Alignment and Analysis of a Disparately Acquired Multibatch Metabolomics Study of Maternal Pregnancy Samples.
Habra H; Kachman M; Padmanabhan V; Burant C; Karnovsky A; Meijer J
J Proteome Res; 2022 Dec; 21(12):2936-2946. PubMed ID: 36367990
[TBL] [Abstract][Full Text] [Related]
4. Data Processing for GC-MS- and LC-MS-Based Untargeted Metabolomics.
Yao L; Sheflin AM; Broeckling CD; Prenni JE
Methods Mol Biol; 2019; 1978():287-299. PubMed ID: 31119670
[TBL] [Abstract][Full Text] [Related]
5. G-Aligner: a graph-based feature alignment method for untargeted LC-MS-based metabolomics.
Wang R; Lu M; An S; Wang J; Yu C
BMC Bioinformatics; 2023 Nov; 24(1):431. PubMed ID: 37964228
[TBL] [Abstract][Full Text] [Related]
6. Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Datasets.
Climaco Pinto R; Karaman I; Lewis MR; Hällqvist J; Kaluarachchi M; Graça G; Chekmeneva E; Durainayagam B; Ghanbari M; Ikram MA; Zetterberg H; Griffin J; Elliott P; Tzoulaki I; Dehghan A; Herrington D; Ebbels T
Anal Chem; 2022 Apr; 94(14):5493-5503. PubMed ID: 35360896
[TBL] [Abstract][Full Text] [Related]
7. Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets.
Hoffmann N; Keck M; Neuweger H; Wilhelm M; Högy P; Niehaus K; Stoye J
BMC Bioinformatics; 2012 Aug; 13():214. PubMed ID: 22920415
[TBL] [Abstract][Full Text] [Related]
8. Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction.
Brunius C; Shi L; Landberg R
Metabolomics; 2016; 12(11):173. PubMed ID: 27746707
[TBL] [Abstract][Full Text] [Related]
9. Batch alignment via retention orders for preprocessing large-scale multi-batch LC-MS experiments.
Malinka F; Zareie A; Prochazka J; Sedlacek R; Novosadova V
Bioinformatics; 2022 Aug; 38(15):3759-3767. PubMed ID: 35748696
[TBL] [Abstract][Full Text] [Related]
10. Automated Annotation of Untargeted All-Ion Fragmentation LC-MS Metabolomics Data with MetaboAnnotatoR.
Graça G; Cai Y; Lau CE; Vorkas PA; Lewis MR; Want EJ; Herrington D; Ebbels TMD
Anal Chem; 2022 Mar; 94(8):3446-3455. PubMed ID: 35180347
[TBL] [Abstract][Full Text] [Related]
11. peakPantheR, an R package for large-scale targeted extraction and integration of annotated metabolic features in LC-MS profiling datasets.
Wolfer AM; D S Correia G; Sands CJ; Camuzeaux S; Yuen AHY; Chekmeneva E; Takáts Z; Pearce JTM; Lewis MR
Bioinformatics; 2021 Dec; 37(24):4886-4888. PubMed ID: 34125879
[TBL] [Abstract][Full Text] [Related]
12. compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets.
Edmands WM; Petrick L; Barupal DK; Scalbert A; Wilson MJ; Wickliffe JK; Rappaport SM
Anal Chem; 2017 Apr; 89(7):3919-3928. PubMed ID: 28225587
[TBL] [Abstract][Full Text] [Related]
13. Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data.
Hemmer S; Manier SK; Fischmann S; Westphal F; Wagmann L; Meyer MR
Metabolites; 2020 Sep; 10(9):. PubMed ID: 32967365
[TBL] [Abstract][Full Text] [Related]
14. ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets.
Gorrochategui E; Jaumot J; Tauler R
BMC Bioinformatics; 2019 May; 20(1):256. PubMed ID: 31101001
[TBL] [Abstract][Full Text] [Related]
15. A Simple Method for Peak Alignment Using Relative Retention Time Related to an Inherent Peak in Liquid Chromatography-Mass Spectrometry-Based Metabolomics.
Wang Y; Ma L; Zhang M; Chen M; Li P; He C; Yan C; Wan JB
J Chromatogr Sci; 2019 Jan; 57(1):9-16. PubMed ID: 30084945
[TBL] [Abstract][Full Text] [Related]
16. Comparison of peak-picking workflows for untargeted liquid chromatography/high-resolution mass spectrometry metabolomics data analysis.
Rafiei A; Sleno L
Rapid Commun Mass Spectrom; 2015 Jan; 29(1):119-27. PubMed ID: 25462372
[TBL] [Abstract][Full Text] [Related]
17. 3D-MSNet: a point cloud-based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data.
Wang R; Lu M; An S; Wang J; Yu C
Bioinformatics; 2023 May; 39(5):. PubMed ID: 37071700
[TBL] [Abstract][Full Text] [Related]
18. Disparate Metabolomics Data Reassembler: A Novel Algorithm for Agglomerating Incongruent LC-MS Metabolomics Datasets.
Mak TD; Goudarzi M; Laiakis EC; Stein SE
Anal Chem; 2020 Apr; 92(7):5231-5239. PubMed ID: 32118408
[TBL] [Abstract][Full Text] [Related]
19. Shape-based feature matching improves protein identification via LC-MS and tandem MS.
Noy K; Towfic F; Wittenberg GM; Fasulo D
J Comput Biol; 2011 Apr; 18(4):547-57. PubMed ID: 21417940
[TBL] [Abstract][Full Text] [Related]
20. Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography-Mass Spectroscopy (LC-MS) Data Processing.
DeFelice BC; Mehta SS; Samra S; Čajka T; Wancewicz B; Fahrmann JF; Fiehn O
Anal Chem; 2017 Mar; 89(6):3250-3255. PubMed ID: 28225594
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
