BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

581 related articles for article (PubMed ID: 32962626)

  • 1. Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.
    Xu D; Zhang J; Xu H; Zhang Y; Chen W; Gao R; Dehmer M
    BMC Genomics; 2020 Sep; 21(1):650. PubMed ID: 32962626
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma.
    Abdelwahab O; Awad N; Elserafy M; Badr E
    PLoS One; 2022; 17(9):e0269126. PubMed ID: 36067196
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods.
    Chen JW; Dhahbi J
    Sci Rep; 2021 Jun; 11(1):13323. PubMed ID: 34172784
    [TBL] [Abstract][Full Text] [Related]  

  • 4. EMT network-based feature selection improves prognosis prediction in lung adenocarcinoma.
    Shao B; Bjaanæs MM; Helland Å; Schütte C; Conrad T
    PLoS One; 2019; 14(1):e0204186. PubMed ID: 30703089
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.
    Li Y; Ge D; Gu J; Xu F; Zhu Q; Lu C
    BMC Cancer; 2019 Sep; 19(1):886. PubMed ID: 31488089
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study.
    Li Y; Mansmann U; Du S; Hornung R
    Genes (Basel); 2021 Nov; 12(12):. PubMed ID: 34946821
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Feature selection for genomic data sets through feature clustering.
    Zheng F; Shen X; Fu Z; Zheng S; Li G
    Int J Data Min Bioinform; 2010; 4(2):228-40. PubMed ID: 20423022
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes.
    Hu F; Zhou Y; Wang Q; Yang Z; Shi Y; Chi Q
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(4):1187-1197. PubMed ID: 30892233
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Feature selection and nearest centroid classification for protein mass spectrometry.
    Levner I
    BMC Bioinformatics; 2005 Mar; 6():68. PubMed ID: 15788095
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Network-based drug sensitivity prediction.
    Ahmed KT; Park S; Jiang Q; Yeu Y; Hwang T; Zhang W
    BMC Med Genomics; 2020 Dec; 13(Suppl 11):193. PubMed ID: 33371891
    [TBL] [Abstract][Full Text] [Related]  

  • 11. caBIG VISDA: modeling, visualization, and discovery for cluster analysis of genomic data.
    Zhu Y; Li H; Miller DJ; Wang Z; Xuan J; Clarke R; Hoffman EP; Wang Y
    BMC Bioinformatics; 2008 Sep; 9():383. PubMed ID: 18801195
    [TBL] [Abstract][Full Text] [Related]  

  • 12. GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.
    Doungpan N; Engchuan W; Chan JH; Meechai A
    BMC Med Genomics; 2016 Dec; 9(Suppl 3):70. PubMed ID: 28117655
    [TBL] [Abstract][Full Text] [Related]  

  • 13. MLW-gcForest: a multi-weighted gcForest model towards the staging of lung adenocarcinoma based on multi-modal genetic data.
    Dong Y; Yang W; Wang J; Zhao J; Qiang Y; Zhao Z; Kazihise NGF; Cui Y; Yang X; Liu S
    BMC Bioinformatics; 2019 Nov; 20(1):578. PubMed ID: 31726986
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A consensus multi-view multi-objective gene selection approach for improved sample classification.
    Acharya S; Cui L; Pan Y
    BMC Bioinformatics; 2020 Sep; 21(Suppl 13):386. PubMed ID: 32938388
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Tailoring pretext tasks to improve self-supervised learning in histopathologic subtype classification of lung adenocarcinomas.
    Ding R; Yadav A; Rodriguez E; Araujo Lemos da Silva AC; Hsu W
    Comput Biol Med; 2023 Nov; 166():107484. PubMed ID: 37741228
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identification of a novel therapeutic candidate, NRK, in primary cancer-associated fibroblasts of lung adenocarcinoma microenvironment.
    Wei T; Song J; Liang K; Li L; Mo X; Huang Z; Chen G; Mao N; Yang J
    J Cancer Res Clin Oncol; 2021 Apr; 147(4):1049-1064. PubMed ID: 33387038
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Association of specific gene mutations derived from machine learning with survival in lung adenocarcinoma.
    Cho HJ; Lee S; Ji YG; Lee DH
    PLoS One; 2018; 13(11):e0207204. PubMed ID: 30419062
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma.
    Toh SH; Prathipati P; Motakis E; Kwoh CK; Yenamandra SP; Kuznetsov VA
    BMC Genomics; 2011 Nov; 12 Suppl 3(Suppl 3):S24. PubMed ID: 22369099
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Tri-Stage Wrapper-Filter Feature Selection Framework for Disease Classification.
    Mandal M; Singh PK; Ijaz MF; Shafi J; Sarkar R
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34451013
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders.
    Álvarez JD; Matias-Guiu JA; Cabrera-Martín MN; Risco-Martín JL; Ayala JL
    BMC Bioinformatics; 2019 Oct; 20(1):491. PubMed ID: 31601182
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 30.