494 related articles for article (PubMed ID: 35773742)
1. Identification of hub genes and regulatory networks in histologically unstable carotid atherosclerotic plaque by bioinformatics analysis.
Guo J; Ning Y; Su Z; Guo L; Gu Y
BMC Med Genomics; 2022 Jun; 15(1):145. PubMed ID: 35773742
[TBL] [Abstract][Full Text] [Related]
2. Identification of hub genes in unstable atherosclerotic plaque by conjoint analysis of bioinformatics.
Zhang R; Ji Z; Yao Y; Zuo W; Yang M; Qu Y; Su Y; Ma G; Li Y
Life Sci; 2020 Dec; 262():118517. PubMed ID: 33011223
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. Identification of key genes in ruptured atherosclerotic plaques by weighted gene correlation network analysis.
Xu BF; Liu R; Huang CX; He BS; Li GY; Sun HS; Feng ZP; Bao MH
Sci Rep; 2020 Jul; 10(1):10847. PubMed ID: 32616722
[TBL] [Abstract][Full Text] [Related]
6. IGFBP6 Is Downregulated in Unstable Carotid Atherosclerotic Plaques According to an Integrated Bioinformatics Analysis and Experimental Verification.
Liu Y; Huan W; Wu J; Zou S; Qu L
J Atheroscler Thromb; 2020 Oct; 27(10):1068-1085. PubMed ID: 32037372
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Bioinformatic Identification of the Pyroptosis-Related Transcription Factor-MicroRNA-Target Gene Regulatory Network in Angiotensin II-Induced Cardiac Remodeling and Validation of Key Components.
Huang T; Ding J; Lin L; Han L; Yu L; Li M
Front Biosci (Landmark Ed); 2023 Nov; 28(11):293. PubMed ID: 38062833
[TBL] [Abstract][Full Text] [Related]
9. Identification of microRNA-mRNA-TF regulatory networks in periodontitis by bioinformatics analysis.
Gao X; Zhao D; Han J; Zhang Z; Wang Z
BMC Oral Health; 2022 Apr; 22(1):118. PubMed ID: 35397550
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Identification of key microRNAs and genes associated with abdominal aortic aneurysm based on the gene expression profile.
Yang P; Cai Z; Wu K; Hu Y; Liu L; Liao M
Exp Physiol; 2020 Jan; 105(1):160-173. PubMed ID: 31553078
[TBL] [Abstract][Full Text] [Related]
13. Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis.
Tan X; Zhang X; Pan L; Tian X; Dong P
Biomed Res Int; 2017; 2017():4323496. PubMed ID: 29226137
[TBL] [Abstract][Full Text] [Related]
14. Identification of a Potential MiRNA-mRNA Regulatory Network for Osteoporosis by Using Bioinformatics Methods: A Retrospective Study Based on the Gene Expression Omnibus Database.
Lin S; Wu J; Chen B; Li S; Huang H
Front Endocrinol (Lausanne); 2022; 13():844218. PubMed ID: 35620387
[TBL] [Abstract][Full Text] [Related]
15. Identification of Potential Key Genes Involved in the Carotid Atherosclerosis.
Meng Y; Zhang C; Liang L; Wei L; Wang H; Zhou F; Li R; Zou D; Huang X; Liu J
Clin Interv Aging; 2021; 16():1071-1084. PubMed ID: 34140767
[TBL] [Abstract][Full Text] [Related]
16. Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes associated with prostate cancer.
Ye Y; Li SL; Wang SY
PLoS One; 2018; 13(8):e0198055. PubMed ID: 30138363
[TBL] [Abstract][Full Text] [Related]
17. Identifying possible hub genes and biological mechanisms shared between bladder cancer and inflammatory bowel disease using machine learning and integrated bioinformatics.
Liu J; Wu P; Lai S; Wang J; Wang J; Zhang Y
J Cancer Res Clin Oncol; 2023 Dec; 149(18):16885-16904. PubMed ID: 37740761
[TBL] [Abstract][Full Text] [Related]
18. Bioinformatics Analysis of Choriocarcinoma-Related MicroRNA-Transcription Factor-Target Gene Regulatory Networks and Validation of Key miRNAs.
Peng X; Zhang Z; Mo Y; Liu J; Wang S; Liu H
Onco Targets Ther; 2021; 14():3903-3919. PubMed ID: 34234459
[TBL] [Abstract][Full Text] [Related]
19. Comparative analysis of gene expression between mice and humans in acetaminophen-induced liver injury by integrating bioinformatics analysis.
Zhao S; Feng Y; Zhang J; Zhang Q; Wang J; Cui S
BMC Med Genomics; 2024 Mar; 17(1):80. PubMed ID: 38549107
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]