145 related articles for article (PubMed ID: 36046382)
1. Exploring Key Genes and Pathways of Cardiac Hypertrophy Based on Bioinformatics.
Zhang Z; Wang C
Dis Markers; 2022; 2022():2081590. PubMed ID: 36046382
[TBL] [Abstract][Full Text] [Related]
2. Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.
Zhang K; Kong X; Feng G; Xiang W; Chen L; Yang F; Cao C; Ding Y; Chen H; Chu M; Wang P; Zhang B
J Ovarian Res; 2018 Feb; 11(1):16. PubMed ID: 29482638
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Identification of key genes and pathways in pelvic organ prolapse based on gene expression profiling by bioinformatics analysis.
Zhou Q; Hong L; Wang J
Arch Gynecol Obstet; 2018 May; 297(5):1323-1332. PubMed ID: 29546564
[TBL] [Abstract][Full Text] [Related]
5. Integrated microarray analysis to identify potential biomarkers and therapeutic targets in dilated cardiomyopathy.
Zhang H; Huo J; Jiang W; Shan Q
Mol Med Rep; 2020 Aug; 22(2):915-925. PubMed ID: 32626989
[TBL] [Abstract][Full Text] [Related]
6. Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.
Gao ZY; Su LC; Wu QC; Sheng JE; Wang YL; Dai YF; Chen AP; He SS; Huang X; Yan GQ
Clin Rheumatol; 2022 Feb; 41(2):437-452. PubMed ID: 34553293
[TBL] [Abstract][Full Text] [Related]
7. Identification of Potential Genetic Biomarkers and Target Genes of Peri-Implantitis Using Bioinformatics Tools.
Zhang X; Wang Z; Hu L; Shen X; Liu C
Biomed Res Int; 2021; 2021():1759214. PubMed ID: 34931168
[TBL] [Abstract][Full Text] [Related]
8. 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; 13(1):10. PubMed ID: 31987036
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis.
Xiong Y; Mi BB; Liu MF; Xue H; Wu QP; Liu GH
Med Sci Monit; 2019 Mar; 25():2246-2256. PubMed ID: 30916045
[TBL] [Abstract][Full Text] [Related]
11. Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis.
Song Y; Feng T; Cao W; Yu H; Zhang Z
Comput Intell Neurosci; 2022; 2022():9022700. PubMed ID: 35712071
[TBL] [Abstract][Full Text] [Related]
12. 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; 15(1):7. PubMed ID: 35016690
[TBL] [Abstract][Full Text] [Related]
13. Study on potential differentially expressed genes in stroke by bioinformatics analysis.
Yang X; Wang P; Yan S; Wang G
Neurol Sci; 2022 Feb; 43(2):1155-1166. PubMed ID: 34313877
[TBL] [Abstract][Full Text] [Related]
14. Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer.
Yang C; Gong A
Int J Med Sci; 2021; 18(3):792-800. PubMed ID: 33437215
[No Abstract] [Full Text] [Related]
15. The identification of a common different gene expression signature in patients with colorectal cancer.
Zhao ZW; Fan XX; Yang LL; Song JJ; Fang SJ; Tu JF; Chen MJ; Zheng LY; Wu FZ; Zhang DK; Ying XH; Ji JS
Math Biosci Eng; 2019 Apr; 16(4):2942-2958. PubMed ID: 31137244
[TBL] [Abstract][Full Text] [Related]
16. Identification of Key Biomarkers and Potential Molecular Mechanisms in Renal Cell Carcinoma by Bioinformatics Analysis.
Li F; Guo P; Dong K; Guo P; Wang H; Lv X
J Comput Biol; 2019 Nov; 26(11):1278-1295. PubMed ID: 31233342
[No Abstract] [Full Text] [Related]
17. Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.
Zhang P; Feng J; Wu X; Chu W; Zhang Y; Li P
Pathol Oncol Res; 2021; 27():588532. PubMed ID: 34257537
[No Abstract] [Full Text] [Related]
18. Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis.
Yang B; Dong K; Guo P; Guo P; Jie G; Zhang G; Li T
J Comput Biol; 2020 Jan; 27(1):40-54. PubMed ID: 31424263
[TBL] [Abstract][Full Text] [Related]
19. The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.
Zhang C; Peng L; Zhang Y; Liu Z; Li W; Chen S; Li G
Med Oncol; 2017 Jun; 34(6):101. PubMed ID: 28432618
[TBL] [Abstract][Full Text] [Related]
20. Analysis of genes associated with prognosis of lung adenocarcinoma based on GEO and TCGA databases.
Yu Y; Tian X
Medicine (Baltimore); 2020 May; 99(19):e20183. PubMed ID: 32384511
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
