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113 related items for PubMed ID: 25412665

  • 1. Constructing protein-protein interaction network of hypertension with blood stasis syndrome via digital gene expression sequencing and database mining.
    Lian YH, Fang MX, Chen LG.
    J Integr Med; 2014 Nov; 12(6):476-82. PubMed ID: 25412665
    [Abstract] [Full Text] [Related]

  • 2. Differential gene expression profiles in coronary heart disease patients of blood stasis syndrome in traditional Chinese medicine and clinical role of target gene.
    Ma XJ, Yin HJ, Chen KJ.
    Chin J Integr Med; 2009 Apr; 15(2):101-6. PubMed ID: 19407946
    [Abstract] [Full Text] [Related]

  • 3. [The screening and the functional pathway analysis of differential genes correlated with coronary heart disease of blood stasis syndrome].
    Yuan ZK, Wang LP, Huang XP.
    Zhongguo Zhong Xi Yi Jie He Za Zhi; 2012 Oct; 32(10):1313-8. PubMed ID: 23163136
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  • 4. Identification of more objective biomarkers for Blood-Stasis syndrome diagnosis.
    Liao J, Liu Y, Wang J.
    BMC Complement Altern Med; 2016 Sep 22; 16(1):371. PubMed ID: 27660006
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  • 5. Transcriptome analysis of blood stasis syndrome in subjects with hypertension.
    He L, Fang M, Chen L, Zhou J, Yuan J, Xu J, Shan Y, Xu Q, Xiong T.
    J Tradit Chin Med; 2016 Apr 22; 36(2):173-80. PubMed ID: 27400471
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  • 6. Bioinformatics analysis of microRNAs related to blood stasis syndrome in diabetes mellitus patients.
    Chen R, Chen M, Xiao Y, Liang Q, Cai Y, Chen L, Fang M.
    Biosci Rep; 2018 Apr 27; 38(2):. PubMed ID: 29437903
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  • 7. Differential expression of microRNA in endothelial cells incubated with serum of hypertension patients with blood-stasis syndrome.
    Wang MM, Fang MX, Chen LG, Wang HQ, Liu HJ, Tang HL.
    Chin J Integr Med; 2015 Nov 27; 21(11):817-22. PubMed ID: 25864118
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  • 12. Identification of key genes and crucial modules associated with coronary artery disease by bioinformatics analysis.
    Zhang X, Cheng X, Liu H, Zheng C, Rao K, Fang Y, Zhou H, Xiong S.
    Int J Mol Med; 2014 Sep 27; 34(3):863-9. PubMed ID: 24969630
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  • 14. Integration of anatomy ontology data with protein-protein interaction networks improves the candidate gene prediction accuracy for anatomical entities.
    Fernando PC, Mabee PM, Zeng E.
    BMC Bioinformatics; 2020 Oct 07; 21(1):442. PubMed ID: 33028186
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  • 18. Comprehensive analysis of gene-expression profile in chronic obstructive pulmonary disease.
    Wei L, Xu D, Qian Y, Huang G, Ma W, Liu F, Shen Y, Wang Z, Li L, Zhang S, Chen Y.
    Int J Chron Obstruct Pulmon Dis; 2015 Oct 07; 10():1103-9. PubMed ID: 26089660
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  • 20. Integrated analysis of differentially expressed genes and pathways in triple‑negative breast cancer.
    Peng C, Ma W, Xia W, Zheng W.
    Mol Med Rep; 2017 Mar 07; 15(3):1087-1094. PubMed ID: 28075450
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