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Journal Abstract Search

197 related items for PubMed ID: 35721731

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  • 5. Diabetic kidney disease-predisposing proinflammatory and profibrotic genes identified by weighted gene co-expression network analysis (WGCNA).
    Chen J, Luo SF, Yuan X, Wang M, Yu HJ, Zhang Z, Yang YY.
    J Cell Biochem; 2022 Feb; 123(2):481-492. PubMed ID: 34908186
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  • 11. Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis.
    Hong SY, Xia QD, Xu JZ, Liu CQ, Sun JX, Xun Y, Wang SG.
    BMC Med Genomics; 2022 Jan 11; 15(1):7. PubMed ID: 35016690
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  • 12. Identifying C1QB, ITGAM, and ITGB2 as potential diagnostic candidate genes for diabetic nephropathy using bioinformatics analysis.
    Hu Y, Yu Y, Dong H, Jiang W.
    PeerJ; 2023 Jan 11; 11():e15437. PubMed ID: 37250717
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  • 17. Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis.
    Wen P, Chidanguro T, Shi Z, Gu H, Wang N, Wang T, Li Y, Gao J.
    Mol Med Rep; 2018 Aug 11; 18(2):1538-1550. PubMed ID: 29845250
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  • 18. [Bioinformatics Analysis of Core Genes and Key Pathways in Myelodysplastic Syndrome].
    Wang Y, Wang YS, Hu NB, Teng GS, Zhou Y, Bai J.
    Zhongguo Shi Yan Xue Ye Xue Za Zhi; 2022 Jun 11; 30(3):804-812. PubMed ID: 35680809
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  • 19. Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer.
    Yang D, He Y, Wu B, Deng Y, Wang N, Li M, Liu Y.
    J Ovarian Res; 2020 Jan 27; 13(1):10. PubMed ID: 31987036
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  • 20. Identification of hub genes associated with acute kidney injury induced by renal ischemia-reperfusion injury in mice.
    He S, He L, Yan F, Li J, Liao X, Ling M, Jing R, Pan L.
    Front Physiol; 2022 Jan 27; 13():951855. PubMed ID: 36246123
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