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 *

124 related articles for article (PubMed ID: 38007754)

  • 1. A Prognostic Model of Genetic Markers for Triple-Negative Breast Cancer Based on Machine Learning and Bioinformatics Analysis.
    Guan H; Su Y; Guo W; Chen C; Xie X; Lv X
    Stud Health Technol Inform; 2023 Nov; 308():303-312. PubMed ID: 38007754
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis.
    Chen DL; Cai JH; Wang CCN
    Genes (Basel); 2022 May; 13(5):. PubMed ID: 35627287
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.
    Ma J; Chen C; Liu S; Ji J; Wu D; Huang P; Wei D; Fan Z; Ren L
    Cancer Gene Ther; 2022 Nov; 29(11):1578-1589. PubMed ID: 35474355
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Identification of differentially expressed genes between triple and non-triple-negative breast cancer using bioinformatics analysis.
    Zhai Q; Li H; Sun L; Yuan Y; Wang X
    Breast Cancer; 2019 Nov; 26(6):784-791. PubMed ID: 31197620
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers.
    Liu Y; Teng L; Fu S; Wang G; Li Z; Ding C; Wang H; Bi L
    BMC Cancer; 2021 May; 21(1):644. PubMed ID: 34053447
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis.
    Zhong G; Lou W; Shen Q; Yu K; Zheng Y
    Mol Med Rep; 2020 Feb; 21(2):557-566. PubMed ID: 31974598
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Machine Learning Model to Predict the Triple Negative Breast Cancer Immune Subtype.
    Chen Z; Wang M; De Wilde RL; Feng R; Su M; Torres-de la Roche LA; Shi W
    Front Immunol; 2021; 12():749459. PubMed ID: 34603338
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning analysis identifies genes differentiating triple negative breast cancers.
    Kothari C; Osseni MA; Agbo L; Ouellette G; Déraspe M; Laviolette F; Corbeil J; Lambert JP; Diorio C; Durocher F
    Sci Rep; 2020 Jun; 10(1):10464. PubMed ID: 32591639
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification and Validation of a Novel Glycolysis-Related Gene Signature for Predicting the Prognosis and Therapeutic Response in Triple-Negative Breast Cancer.
    Zheng J; Zhang YF; Han GH; Fan MY; Du MH; Zhang GC; Zhang B; Qiao J; Zhang SX; Cao JM
    Adv Ther; 2023 Jan; 40(1):310-330. PubMed ID: 36316558
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Novel biomarkers identified in triple-negative breast cancer through RNA-sequencing.
    Chen YL; Wang K; Xie F; Zhuo ZL; Liu C; Yang Y; Wang S; Zhao XT
    Clin Chim Acta; 2022 Jun; 531():302-308. PubMed ID: 35504321
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer.
    Yang X; Weng X; Yang Y; Zhang M; Xiu Y; Peng W; Liao X; Xu M; Sun Y; Liu X
    Aging (Albany NY); 2021 Aug; 13(15):19486-19509. PubMed ID: 34341184
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer.
    Naorem LD; Muthaiyan M; Venkatesan A
    J Cell Biochem; 2019 Apr; 120(4):6154-6167. PubMed ID: 30302816
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prognostic Alternative mRNA Splicing Signature and a Novel Biomarker in Triple-Negative Breast Cancer.
    Liu Q; Wang X; Kong X; Yang X; Cheng R; Zhang W; Gao P; Chen L; Wang Z; Fang Y; Wang J
    DNA Cell Biol; 2020 Jun; 39(6):1051-1063. PubMed ID: 32379494
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning assisted analysis of breast cancer gene expression profiles reveals novel potential prognostic biomarkers for triple-negative breast cancer.
    Thalor A; Kumar Joon H; Singh G; Roy S; Gupta D
    Comput Struct Biotechnol J; 2022; 20():1618-1631. PubMed ID: 35465161
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Screening of DNA Damage Repair Genes Involved in the Prognosis of Triple-Negative Breast Cancer Patients Based on Bioinformatics.
    Wang N; Gu Y; Chi J; Liu X; Xiong Y; Zhong C; Wang F; Wang X; Li L
    Front Genet; 2021; 12():721873. PubMed ID: 34408776
    [No Abstract]   [Full Text] [Related]  

  • 16. A novel model associated with tumor microenvironment on predicting prognosis and immunotherapy in triple negative breast cancer.
    Zhang J; Zhang M; Tian Q; Yang J
    Clin Exp Med; 2023 Nov; 23(7):3867-3881. PubMed ID: 37219794
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer.
    Fan CN; Ma L; Liu N
    J Cell Biochem; 2019 Mar; 120(3):3185-3196. PubMed ID: 30203490
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Expression of CD22 in Triple-Negative Breast Cancer: A Novel Prognostic Biomarker and Potential Target for CAR Therapy.
    Zaib T; Cheng K; Liu T; Mei R; Liu Q; Zhou X; He L; Rashid H; Xie Q; Khan H; Xu Y; Sun P; Wu J
    Int J Mol Sci; 2023 Jan; 24(3):. PubMed ID: 36768478
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrating machine learning algorithms to systematically assess reactive oxygen species levels to aid prognosis and novel treatments for triple -negative breast cancer patients.
    Li J; Liang Y; Zhao X; Wu C
    Front Immunol; 2023; 14():1196054. PubMed ID: 37404810
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Tumor Mutation Burden and Immune Invasion Characteristics in Triple Negative Breast Cancer: Genome High-Throughput Data Analysis.
    Gao C; Li H; Liu C; Xu X; Zhuang J; Zhou C; Liu L; Feng F; Sun C
    Front Immunol; 2021; 12():650491. PubMed ID: 33968045
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.