These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

157 related articles for article (PubMed ID: 34981111)

  • 1. TIGER: technical variation elimination for metabolomics data using ensemble learning architecture.
    Han S; Huang J; Foppiano F; Prehn C; Adamski J; Suhre K; Li Y; Matullo G; Schliess F; Gieger C; Peters A; Wang-Sattler R
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 34981111
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MetaClean: a machine learning-based classifier for reduced false positive peak detection in untargeted LC-MS metabolomics data.
    Chetnik K; Petrick L; Pandey G
    Metabolomics; 2020 Oct; 16(11):117. PubMed ID: 33085002
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Instrumental Drift in Untargeted Metabolomics: Optimizing Data Quality with Intrastudy QC Samples.
    Märtens A; Holle J; Mollenhauer B; Wegner A; Kirwan J; Hiller K
    Metabolites; 2023 May; 13(5):. PubMed ID: 37233706
    [TBL] [Abstract][Full Text] [Related]  

  • 4. pseudoQC: A Regression-Based Simulation Software for Correction and Normalization of Complex Metabolomics and Proteomics Datasets.
    Wang S; Yang H
    Proteomics; 2019 Oct; 19(19):e1900264. PubMed ID: 31474000
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics.
    Liu Y; Smirnov K; Lucio M; Gougeon RD; Alexandre H; Schmitt-Kopplin P
    BMC Bioinformatics; 2016 Mar; 17():114. PubMed ID: 26936354
    [TBL] [Abstract][Full Text] [Related]  

  • 6. NormalizeMets: assessing, selecting and implementing statistical methods for normalizing metabolomics data.
    De Livera AM; Olshansky G; Simpson JA; Creek DJ
    Metabolomics; 2018 Mar; 14(5):54. PubMed ID: 30830328
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data.
    Al-Akwaa FM; Yunits B; Huang S; Alhajaji H; Garmire LX
    Gigascience; 2018 Dec; 7(12):. PubMed ID: 30535020
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification.
    Mendez KM; Reinke SN; Broadhurst DI
    Metabolomics; 2019 Nov; 15(12):150. PubMed ID: 31728648
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Application of ensemble deep neural network to metabolomics studies.
    Asakura T; Date Y; Kikuchi J
    Anal Chim Acta; 2018 Dec; 1037():230-236. PubMed ID: 30292297
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Untargeted metabolomics of fresh and heat treatment Tiger nut (Cyperus esculentus L.) milks reveals further insight into food quality and nutrition.
    Rubert J; Monforte A; Hurkova K; Pérez-Martínez G; Blesa J; Navarro JL; Stranka M; Soriano JM; Hajslova J
    J Chromatogr A; 2017 Sep; 1514():80-87. PubMed ID: 28768579
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Regularized adversarial learning for normalization of multi-batch untargeted metabolomics data.
    Dmitrenko A; Reid M; Zamboni N
    Bioinformatics; 2023 Mar; 39(3):. PubMed ID: 36825815
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reproducibility of mass spectrometry based metabolomics data.
    Ghosh T; Philtron D; Zhang W; Kechris K; Ghosh D
    BMC Bioinformatics; 2021 Sep; 22(1):423. PubMed ID: 34493210
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Quantitative Metabolomics in Alzheimer's Disease: Technical Considerations for Improved Reproducibility.
    Veiga S; Wahrheit J; Rodríguez-Martín A; Sonntag D
    Methods Mol Biol; 2018; 1779():463-470. PubMed ID: 29886550
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Untargeted metabolomics reveals links between Tiger nut (Cyperus esculentus L.) and its geographical origin by metabolome changes associated with membrane lipids.
    Rubert J; Hurkova K; Stranska M; Hajslova J
    Food Addit Contam Part A Chem Anal Control Expo Risk Assess; 2018 Apr; 35(4):605-613. PubMed ID: 29098962
    [TBL] [Abstract][Full Text] [Related]  

  • 15. EPX: An R package for the ensemble of subsets of variables for highly unbalanced binary classification.
    Hsu GG; Tomal JH; Welch WJ
    Comput Biol Med; 2021 Sep; 136():104760. PubMed ID: 34416572
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Improving machine learning with ensemble learning on observational healthcare data.
    Naderalvojoud B; Hernandez-Boussard T
    AMIA Annu Symp Proc; 2023; 2023():521-529. PubMed ID: 38222353
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Extending the Dynamic Range in Metabolomics Experiments by Automatic Correction of Peaks Exceeding the Detection Limit.
    Lisec J; Hoffmann F; Schmitt C; Jaeger C
    Anal Chem; 2016 Aug; 88(15):7487-92. PubMed ID: 27377477
    [TBL] [Abstract][Full Text] [Related]  

  • 18. WaveICA 2.0: a novel batch effect removal method for untargeted metabolomics data without using batch information.
    Deng K; Zhao F; Rong Z; Cao L; Zhang L; Li K; Hou Y; Zhu ZJ
    Metabolomics; 2021 Sep; 17(10):87. PubMed ID: 34542717
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A random forest based biomarker discovery and power analysis framework for diagnostics research.
    Acharjee A; Larkman J; Xu Y; Cardoso VR; Gkoutos GV
    BMC Med Genomics; 2020 Nov; 13(1):178. PubMed ID: 33228632
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 8.