217 related articles for article (PubMed ID: 36383109)
1. Identifying Diagnostic and Prognostic Differentially Expressed Genes of Gastric Cancer Based on Bioinformatics Analyses of RNA-seq Data.
Wang M; Jiang X; Xu S; Deng Y; Cao T; Cheng Y; Zhang WH; Zhang L; Hu J
Genet Test Mol Biomarkers; 2022 Nov; 26(11):512-521. PubMed ID: 36383109
[No Abstract] [Full Text] [Related]
2. 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]
3. The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics.
Ding C; Zhang Q; Jiang X; Wei D; Xu S; Li Q; Wu M; Wang H
Comput Math Methods Med; 2022; 2022():4321466. PubMed ID: 35756405
[TBL] [Abstract][Full Text] [Related]
4. Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gastric cancer.
Wu Q; Zhang B; Wang Z; Hu X; Sun Y; Xu R; Chen X; Wang Q; Ju F; Ren S; Zhang C; Qi F; Ma Q; Xue Q; Zhou YL
Pathol Res Pract; 2019 May; 215(5):1038-1048. PubMed ID: 30975489
[TBL] [Abstract][Full Text] [Related]
5. Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis.
Reyimu A; Chen Y; Song X; Zhou W; Dai J; Jiang F
World J Surg Oncol; 2021 Aug; 19(1):240. PubMed ID: 34384424
[TBL] [Abstract][Full Text] [Related]
6. Identification of Hub Genes and Pathways in Gastric Adenocarcinoma Based on Bioinformatics Analysis.
Qiu J; Sun M; Wang Y; Chen B
Med Sci Monit; 2020 Feb; 26():e920261. PubMed ID: 32058995
[TBL] [Abstract][Full Text] [Related]
7. FN1, SPARC, and SERPINE1 are highly expressed and significantly related to a poor prognosis of gastric adenocarcinoma revealed by microarray and bioinformatics.
Li L; Zhu Z; Zhao Y; Zhang Q; Wu X; Miao B; Cao J; Fei S
Sci Rep; 2019 May; 9(1):7827. PubMed ID: 31127138
[TBL] [Abstract][Full Text] [Related]
8. Bioinformatics analysis suggests that COL4A1 may play an important role in gastric carcinoma recurrence.
Li F; Wang NN; Chang X; Wang SL; Wang LS; Yao J; Li ZS; Bai Y
J Dig Dis; 2019 Aug; 20(8):391-400. PubMed ID: 31069993
[TBL] [Abstract][Full Text] [Related]
9. Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis.
Li T; Gao X; Han L; Yu J; Li H
World J Surg Oncol; 2018 Jun; 16(1):114. PubMed ID: 29921304
[TBL] [Abstract][Full Text] [Related]
10. Bioinformatics analysis identifies coagulation factor II receptor as a potential biomarker in stomach adenocarcinoma.
Wu X; Wang S; Wang C; Wu C; Zhao Z
Sci Rep; 2024 Jan; 14(1):2468. PubMed ID: 38291086
[TBL] [Abstract][Full Text] [Related]
11. Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis.
Li D; Yin Y; He M; Wang J
Med Sci Monit; 2021 Feb; 27():e929104. PubMed ID: 33582701
[TBL] [Abstract][Full Text] [Related]
12. Identification of novel biomarkers, MUC5AC, MUC1, KRT7, GAPDH, CD44 for gastric cancer.
Yang J
Med Oncol; 2020 Mar; 37(5):34. PubMed ID: 32219571
[TBL] [Abstract][Full Text] [Related]
13. Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer.
Yin LK; Yuan HY; Liu JJ; Xu XL; Wang W; Bai XY; Wang P
World J Clin Cases; 2023 Jul; 11(20):4763-4787. PubMed ID: 37584004
[TBL] [Abstract][Full Text] [Related]
14. Microarray profile analysis identifies ETS1 as potential biomarker regulated by miR-23b and modulates TCF4 in gastric cancer.
Mei D; Qi Y; Xia Y; Ma J; Hu H; Ai J; Chen L; Wu N; Liao D
World J Surg Oncol; 2021 Oct; 19(1):311. PubMed ID: 34686186
[TBL] [Abstract][Full Text] [Related]
15. Identification of DNA methylation-regulated differentially-expressed genes and related pathways using Illumina 450K BeadChip and bioinformatic analysis in gastric cancer.
Liang Y; Zhang C; Dai DQ
Pathol Res Pract; 2019 Oct; 215(10):152570. PubMed ID: 31378454
[TBL] [Abstract][Full Text] [Related]
16. Identification of potential core genes in gastric cancer using bioinformatics analysis.
Shao C; Wang R; Kong D; Gao Q; Xu C
J Gastrointest Oncol; 2021 Oct; 12(5):2109-2122. PubMed ID: 34790378
[TBL] [Abstract][Full Text] [Related]
17. Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis.
Abdolahi F; Shahraki A; Sheervalilou R; Mortazavi SS
BMC Med Genomics; 2023 Dec; 16(1):311. PubMed ID: 38041130
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients.
Zhang C; Zhang CD; Ma MH; Dai DQ
World J Gastroenterol; 2018 Mar; 24(11):1206-1215. PubMed ID: 29568201
[TBL] [Abstract][Full Text] [Related]
20. Identification of six candidate genes for endometrial carcinoma by bioinformatics analysis.
Zhu Y; Shi L; Chen P; Zhang Y; Zhu T
World J Surg Oncol; 2020 Jul; 18(1):161. PubMed ID: 32641130
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
