BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

116 related articles for article (PubMed ID: 31746296)

  • 1. Gene Selection for the Discrimination of Colorectal Cancer.
    Wang W; Xie G; Ren Z; Xie T; Li J
    Curr Mol Med; 2020; 20(6):415-428. PubMed ID: 31746296
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Whale optimized mixed kernel function of support vector machine for colorectal cancer diagnosis.
    Zhao D; Liu H; Zheng Y; He Y; Lu D; Lyu C
    J Biomed Inform; 2019 Apr; 92():103124. PubMed ID: 30796977
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal Cancer.
    Liu X; Bing Z; Wu J; Zhang J; Zhou W; Ni M; Meng Z; Liu S; Tian J; Zhang X; Li Y; Jia S; Guo S
    Med Sci Monit; 2020 Jan; 26():e918906. PubMed ID: 31893510
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer.
    Maurya NS; Kushwaha S; Chawade A; Mani A
    Sci Rep; 2021 Jul; 11(1):14304. PubMed ID: 34253750
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An integrated study on TFs and miRNAs in colorectal cancer metastasis and evaluation of three co-regulated candidate genes as prognostic markers.
    Eskandari E; Mahjoubi F; Motalebzadeh J
    Gene; 2018 Dec; 679():150-159. PubMed ID: 30193961
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Identification of Key Genes in Colorectal Cancer Regulated by miR-34a.
    Wang T; Xu H; Liu X; Chen S; Zhou Y; Zhang X
    Med Sci Monit; 2017 Dec; 23():5735-5743. PubMed ID: 29197895
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Identification of Critical Genes and Five Prognostic Biomarkers Associated with Colorectal Cancer.
    Huang Z; Yang Q; Huang Z
    Med Sci Monit; 2018 Jul; 24():4625-4633. PubMed ID: 29973580
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments.
    Zhang T; Guo J; Gu J; Wang Z; Wang G; Li H; Wang J
    Oncol Rep; 2019 Jan; 41(1):279-291. PubMed ID: 30542696
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The feature selection bias problem in relation to high-dimensional gene data.
    Krawczuk J; Łukaszuk T
    Artif Intell Med; 2016 Jan; 66():63-71. PubMed ID: 26674595
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The identification of a common different gene expression signature in patients with colorectal cancer.
    Zhao ZW; Fan XX; Yang LL; Song JJ; Fang SJ; Tu JF; Chen MJ; Zheng LY; Wu FZ; Zhang DK; Ying XH; Ji JS
    Math Biosci Eng; 2019 Apr; 16(4):2942-2958. PubMed ID: 31137244
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling.
    Martinez-Romero J; Bueno-Fortes S; Martín-Merino M; Ramirez de Molina A; De Las Rivas J
    BMC Genomics; 2018 Dec; 19(Suppl 8):857. PubMed ID: 30537927
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Identification of Genes Related to Clinicopathological Characteristics and Prognosis of Patients with Colorectal Cancer.
    Gao X; Yang J
    DNA Cell Biol; 2020 Apr; 39(4):690-699. PubMed ID: 32027181
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles.
    Li X; Peng S; Chen J; Lü B; Zhang H; Lai M
    Biochem Biophys Res Commun; 2012 Mar; 419(2):148-53. PubMed ID: 22306013
    [TBL] [Abstract][Full Text] [Related]  

  • 15. An efficient statistical feature selection approach for classification of gene expression data.
    Chandra B; Gupta M
    J Biomed Inform; 2011 Aug; 44(4):529-35. PubMed ID: 21241823
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Construction of an miRNA-mRNA regulatory network in colorectal cancer with bioinformatics methods.
    Su Y; Zhang M; Zhang L; Chen S; Zhang D; Zhang X
    Anticancer Drugs; 2019 Jul; 30(6):588-595. PubMed ID: 30601194
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A class imbalance-aware Relief algorithm for the classification of tumors using microarray gene expression data.
    He Y; Zhou J; Lin Y; Zhu T
    Comput Biol Chem; 2019 Jun; 80():121-127. PubMed ID: 30947070
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.
    Chen L; Lu D; Sun K; Xu Y; Hu P; Li X; Xu F
    Gene; 2019 Apr; 692():119-125. PubMed ID: 30654001
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Identification of key genes in colorectal cancer using random walk with restart.
    Cui X; Shen K; Xie Z; Liu T; Zhang H
    Mol Med Rep; 2017 Feb; 15(2):867-872. PubMed ID: 28000901
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of key genes associated with colorectal cancer based on the transcriptional network.
    Chen G; Li H; Niu X; Li G; Han N; Li X; Li G; Liu Y; Sun G; Wang Y; Li Z; Li Q
    Pathol Oncol Res; 2015 Jul; 21(3):719-25. PubMed ID: 25613817
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.