BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 33772663)

  • 1. Discrepancies in metabolomic biomarker identification from patient-derived lung cancer revealed by combined variation in data pre-treatment and imputation methods.
    Miller HA; Emam R; Lynch CM; Bockhorst S; Frieboes HB
    Metabolomics; 2021 Mar; 17(4):37. PubMed ID: 33772663
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Lung cancer survival prediction and biomarker identification with an ensemble machine learning analysis of tumor core biopsy metabolomic data.
    Miller HA; van Berkel VH; Frieboes HB
    Metabolomics; 2022 Jul; 18(8):57. PubMed ID: 35857204
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Two data pre-processing workflows to facilitate the discovery of biomarkers by 2D NMR metabolomics.
    Féraud B; Leenders J; Martineau E; Giraudeau P; Govaerts B; de Tullio P
    Metabolomics; 2019 Apr; 15(4):63. PubMed ID: 30993405
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics.
    Gong Y; Ding W; Wang P; Wu Q; Yao X; Yang Q
    J Chem Inf Model; 2023 Dec; 63(24):7628-7641. PubMed ID: 38079572
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Metabolic profiling of potential lung cancer biomarkers using bronchoalveolar lavage fluid and the integrated direct infusion/ gas chromatography mass spectrometry platform.
    Callejón-Leblic B; García-Barrera T; Grávalos-Guzmán J; Pereira-Vega A; Gómez-Ariza JL
    J Proteomics; 2016 Aug; 145():197-206. PubMed ID: 27255828
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Metabolomic profiling of human lung tumor tissues - nucleotide metabolism as a candidate for therapeutic interventions and biomarkers.
    Moreno P; Jiménez-Jiménez C; Garrido-Rodríguez M; Calderón-Santiago M; Molina S; Lara-Chica M; Priego-Capote F; Salvatierra Á; Muñoz E; Calzado MA
    Mol Oncol; 2018 Oct; 12(10):1778-1796. PubMed ID: 30099851
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Metabolomic Biomarker Identification in Presence of Outliers and Missing Values.
    Kumar N; Hoque MA; Shahjaman M; Islam SM; Mollah MN
    Biomed Res Int; 2017; 2017():2437608. PubMed ID: 28293630
    [TBL] [Abstract][Full Text] [Related]  

  • 8. GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies.
    Wei R; Wang J; Jia E; Chen T; Ni Y; Jia W
    PLoS Comput Biol; 2018 Jan; 14(1):e1005973. PubMed ID: 29385130
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.
    Blasco H; Błaszczyński J; Billaut JC; Nadal-Desbarats L; Pradat PF; Devos D; Moreau C; Andres CR; Emond P; Corcia P; Słowiński R
    J Biomed Inform; 2015 Feb; 53():291-9. PubMed ID: 25499899
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery.
    Zhang F; Zhang Y; Ke C; Li A; Wang W; Yang K; Liu H; Xie H; Deng K; Zhao W; Yang C; Lou G; Hou Y; Li K
    Metabolomics; 2018 Apr; 14(5):65. PubMed ID: 30830339
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Metabolomics workflow for lung cancer: Discovery of biomarkers.
    Tang Y; Li Z; Lazar L; Fang Z; Tang C; Zhao J
    Clin Chim Acta; 2019 Aug; 495():436-445. PubMed ID: 31103622
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Statistics and Machine Learning in Mass Spectrometry-Based Metabolomics Analysis.
    Fan S; Wilson CM; Fridley BL; Li Q
    Methods Mol Biol; 2023; 2629():247-269. PubMed ID: 36929081
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling.
    Di Guida R; Engel J; Allwood JW; Weber RJ; Jones MR; Sommer U; Viant MR; Dunn WB
    Metabolomics; 2016; 12():93. PubMed ID: 27123000
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Missing data imputation via the expectation-maximization algorithm can improve principal component analysis aimed at deriving biomarker profiles and dietary patterns.
    Malan L; Smuts CM; Baumgartner J; Ricci C
    Nutr Res; 2020 Mar; 75():67-76. PubMed ID: 32035304
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets.
    Alcazar O; Ogihara M; Ren G; Buchwald P; Abdulreda MH
    Biomolecules; 2022 Oct; 12(10):. PubMed ID: 36291653
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies.
    Do KT; Wahl S; Raffler J; Molnos S; Laimighofer M; Adamski J; Suhre K; Strauch K; Peters A; Gieger C; Langenberg C; Stewart ID; Theis FJ; Grallert H; Kastenmüller G; Krumsiek J
    Metabolomics; 2018 Sep; 14(10):128. PubMed ID: 30830398
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Missing value imputation strategies for metabolomics data.
    Armitage EG; Godzien J; Alonso-Herranz V; López-Gonzálvez Á; Barbas C
    Electrophoresis; 2015 Dec; 36(24):3050-60. PubMed ID: 26376450
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: a comparative study.
    Kokla M; Virtanen J; Kolehmainen M; Paananen J; Hanhineva K
    BMC Bioinformatics; 2019 Oct; 20(1):492. PubMed ID: 31601178
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics.
    Dekermanjian JP; Shaddox E; Nandy D; Ghosh D; Kechris K
    BMC Bioinformatics; 2022 May; 23(1):179. PubMed ID: 35578165
    [TBL] [Abstract][Full Text] [Related]  

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

    [Next]    [New Search]
    of 9.