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 *

189 related articles for article (PubMed ID: 38609711)

  • 1. Identification of hub genes and diagnostic efficacy for triple-negative breast cancer through WGCNA and Mendelian randomization.
    Lin Y; Wang S; Yang Q
    Discov Oncol; 2024 Apr; 15(1):117. PubMed ID: 38609711
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Functional investigation and two-sample Mendelian randomization study of neuropathic pain hub genes obtained by WGCNA analysis.
    Zeng J; Lai C; Luo J; Li L
    Front Neurosci; 2023; 17():1134330. PubMed ID: 37123369
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identification of potential oncogenes in triple-negative breast cancer based on bioinformatics analyses.
    Xiao X; Zhang Z; Luo R; Peng R; Sun Y; Wang J; Chen X
    Oncol Lett; 2021 May; 21(5):363. PubMed ID: 33747220
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Upregulated cyclins may be novel genes for triple-negative breast cancer based on bioinformatic analysis.
    Lu Y; Yang G; Xiao Y; Zhang T; Su F; Chang R; Ling X; Bai Y
    Breast Cancer; 2020 Sep; 27(5):903-911. PubMed ID: 32338339
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Hsa-mir-3163 and CCNB1 may be potential biomarkers and therapeutic targets for androgen receptor positive triple-negative breast cancer.
    Qiu P; Guo Q; Yao Q; Chen J; Lin J
    PLoS One; 2021; 16(11):e0254283. PubMed ID: 34797837
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Identification of key hub genes in knee osteoarthritis through integrated bioinformatics analysis.
    Xu L; Ma J; Zhou C; Shen Z; Zhu K; Wu X; Chen Y; Chen T; Lin X
    Sci Rep; 2024 Sep; 14(1):22437. PubMed ID: 39341952
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of potential core genes in triple negative breast cancer using bioinformatics analysis.
    Li MX; Jin LT; Wang TJ; Feng YJ; Pan CP; Zhao DM; Shao J
    Onco Targets Ther; 2018; 11():4105-4112. PubMed ID: 30140156
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identification of novel prognostic genes of triple-negative breast cancer using meta-analysis and weighted gene co-expressed network analysis.
    Cao W; Jiang Y; Ji X; Guan X; Lin Q; Ma L
    Ann Transl Med; 2021 Feb; 9(3):205. PubMed ID: 33708832
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Identification of key gene modules and hub genes of human mantle cell lymphoma by coexpression network analysis.
    Guo D; Wang H; Sun L; Liu S; Du S; Qiao W; Wang W; Hou G; Zhang K; Li C; Teng Q
    PeerJ; 2020; 8():e8843. PubMed ID: 32219041
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining.
    Chen J; Liu C; Cen J; Liang T; Xue J; Zeng H; Zhang Z; Xu G; Yu C; Lu Z; Wang Z; Jiang J; Zhan X; Zeng J
    Medicine (Baltimore); 2020 May; 99(18):e19986. PubMed ID: 32358373
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis.
    Deng JL; Xu YH; Wang G
    Front Genet; 2019; 10():695. PubMed ID: 31428132
    [No Abstract]   [Full Text] [Related]  

  • 15. Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis.
    Wei LM; Li XY; Wang ZM; Wang YK; Yao G; Fan JH; Wang XS
    Gland Surg; 2021 Feb; 10(2):799-806. PubMed ID: 33708561
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis.
    Yuan Q; Zheng L; Liao Y; Wu G
    World J Surg Oncol; 2021 Mar; 19(1):86. PubMed ID: 33757543
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Systematic identification of key functional modules and genes in esophageal cancer.
    Wu R; Zhuang H; Mei YK; Sun JY; Dong T; Zhao LL; Fan ZN; Liu L
    Cancer Cell Int; 2021 Feb; 21(1):134. PubMed ID: 33632229
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Evaluation of diagnostic value and Mendelian randomization study of appendicitis hub genes obtained by WGCNA analysis.
    Li LS; Tong Y; Yuan C; Zhang W
    Medicine (Baltimore); 2024 Sep; 103(36):e39307. PubMed ID: 39252332
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Explore Key Genes and Mechanisms Involved in Colon Cancer Progression Based on Bioinformatics Analysis.
    Lan Y; Yang X; Wei Y; Tian Z; Zhang L; Zhou J
    Appl Biochem Biotechnol; 2024 Sep; 196(9):6253-6268. PubMed ID: 38294732
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 10.