503 related articles for article (PubMed ID: 32938406)
1. Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis.
Wang D; Liu B; Xiong T; Yu W; She Q
BMC Cardiovasc Disord; 2020 Sep; 20(1):419. PubMed ID: 32938406
[TBL] [Abstract][Full Text] [Related]
2. Identification of Potential Hub Genes of Atherosclerosis Through Bioinformatic Analysis.
Yin Y; Zou YF; Xiao Y; Wang TX; Wang YN; Dong ZC; Huo YH; Yao BC; Meng LB; Du SX
J Comput Biol; 2021 Jan; 28(1):60-78. PubMed ID: 32286084
[TBL] [Abstract][Full Text] [Related]
3. Investigation of the Underlying Genes and Mechanism of Macrophage-Enriched Ruptured Atherosclerotic Plaques Using Bioinformatics Method.
Wang H; Liu D; Zhang H
J Atheroscler Thromb; 2019 Jul; 26(7):636-658. PubMed ID: 30643084
[TBL] [Abstract][Full Text] [Related]
4. Prediction of genetic risk factors of atherosclerosis using various bioinformatic tools.
Wang HX; Zhao YX
Genet Mol Res; 2016 Apr; 15(2):. PubMed ID: 27173180
[TBL] [Abstract][Full Text] [Related]
5. Analysis of Differentially Expressed Genes and Molecular Pathways in Familial Hypercholesterolemia Involved in Atherosclerosis: A Systematic and Bioinformatics Approach.
Udhaya Kumar S; Thirumal Kumar D; Bithia R; Sankar S; Magesh R; Sidenna M; George Priya Doss C; Zayed H
Front Genet; 2020; 11():734. PubMed ID: 32760426
[No Abstract] [Full Text] [Related]
6. The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis.
Cheng R; Xu X; Yang S; Mi Z; Zhao Y; Gao J; Yu F; Ren X
Eur J Med Res; 2022 Oct; 27(1):212. PubMed ID: 36303246
[TBL] [Abstract][Full Text] [Related]
7. Identification of hub genes in rheumatoid arthritis through an integrated bioinformatics approach.
Wu R; Long L; Zhou Q; Su J; Su W; Zhu J
J Orthop Surg Res; 2021 Jul; 16(1):458. PubMed ID: 34271942
[TBL] [Abstract][Full Text] [Related]
8. Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis.
Kolur V; Vastrad B; Vastrad C; Kotturshetti S; Tengli A
BMC Cardiovasc Disord; 2021 Jul; 21(1):329. PubMed ID: 34218797
[TBL] [Abstract][Full Text] [Related]
9. Identification of potential hub genes and regulatory networks of smoking-related endothelial dysfunction in atherosclerosis using bioinformatics analysis.
Guo J; Ning Y; Pan D; Wu S; Gao X; Wang C; Guo L; Gu Y
Technol Health Care; 2024; 32(3):1781-1794. PubMed ID: 38073349
[TBL] [Abstract][Full Text] [Related]
10. Identification of potential therapeutic targets for plaque vulnerability based on an integrated analysis.
Miao L; Qin YA; Yang ZJ; Shi WX; Wei XQ; Liu Y; Liu YL
Nutr Metab Cardiovasc Dis; 2024 Jul; 34(7):1649-1659. PubMed ID: 38749785
[TBL] [Abstract][Full Text] [Related]
11. Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data.
Vastrad B; Vastrad C; Godavarthi A; Chandrashekar R
Med Oncol; 2017 Sep; 34(11):182. PubMed ID: 28952134
[TBL] [Abstract][Full Text] [Related]
12. Identification of human prolactinoma related genes by DNA microarray.
Zhao L; Lin M; Wang S
J Cancer Res Ther; 2014; 10(3):544-8. PubMed ID: 25313736
[TBL] [Abstract][Full Text] [Related]
13. Cytochrome c oxidase subunit VIIb as a potential target in familial hypercholesterolemia by bioinformatical analysis.
Li G; Wu XJ; Kong XQ; Wang L; Jin X
Eur Rev Med Pharmacol Sci; 2015 Nov; 19(21):4139-45. PubMed ID: 26592840
[TBL] [Abstract][Full Text] [Related]
14. Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma.
Li Y; Zhu YY; Dai GP; Wu DJ; Gao ZZ; Zhang L; Fan YH
Math Biosci Eng; 2019 Nov; 17(1):910-927. PubMed ID: 31731384
[TBL] [Abstract][Full Text] [Related]
15. Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.
Guo T; Hou D; Yu D
Mol Med Rep; 2019 Nov; 20(5):4415-4424. PubMed ID: 31545495
[TBL] [Abstract][Full Text] [Related]
16. Underlying Genes Involved in Atherosclerotic Macrophages: Insights from Microarray Data Mining.
Wang W; Zhang K; Zhang H; Li M; Zhao Y; Wang B; Xin W; Yang W; Zhang J; Yue S; Yang X
Med Sci Monit; 2019 Dec; 25():9949-9962. PubMed ID: 31875420
[TBL] [Abstract][Full Text] [Related]
17. Identification of potential crucial genes associated with early-onset preeclampsia via bioinformatic analysis.
Kang Q; Li W; Xiao J; Yu N; Fan L; Sha M; Ma S; Wu J; Chen S
Pregnancy Hypertens; 2021 Jun; 24():27-36. PubMed ID: 33640831
[TBL] [Abstract][Full Text] [Related]
18. Identification of core genes and pathways in type 2 diabetes mellitus by bioinformatics analysis.
Ding L; Fan L; Xu X; Fu J; Xue Y
Mol Med Rep; 2019 Sep; 20(3):2597-2608. PubMed ID: 31524257
[TBL] [Abstract][Full Text] [Related]
19. Exploring of the molecular mechanism of rhinitis via bioinformatics methods.
Song Y; Yan Z
Mol Med Rep; 2018 Feb; 17(2):3014-3020. PubMed ID: 29257233
[TBL] [Abstract][Full Text] [Related]
20. Bioinformatics Analysis Identifies Hub Genes and Molecular Pathways Involved in Sepsis-Induced Myopathy.
Ning YL; Yang ZQ; Xian SX; Lin JZ; Lin XF; Chen WT
Med Sci Monit; 2020 Feb; 26():e919665. PubMed ID: 32008037
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
