These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
281 related articles for article (PubMed ID: 30134903)
1. Prediction of key genes and pathways involved in trastuzumab-resistant gastric cancer. Yu C; Xue P; Zhang L; Pan R; Cai Z; He Z; Sun J; Zheng M World J Surg Oncol; 2018 Aug; 16(1):174. PubMed ID: 30134903 [TBL] [Abstract][Full Text] [Related]
2. Bioinformatics Analysis of Potential Key Genes in Trastuzumab-Resistant Gastric Cancer. Yang G; Jian L; Lin X; Zhu A; Wen G Dis Markers; 2019; 2019():1372571. PubMed ID: 31949544 [TBL] [Abstract][Full Text] [Related]
3. 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]
4. Five hub genes contributing to the oncogenesis and trastuzumab-resistance in gastric cancer. Chen F; Wang Y; Zhang X; Fang J Gene; 2023 Jan; 851():146942. PubMed ID: 36202277 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. Chemo-resistant Gastric Cancer Associated Gene Expression Signature: Bioinformatics Analysis Based on Gene Expression Omnibus. Liu JB; Jian T; Yue C; Chen D; Chen W; Bao TT; Liu HX; Cao Y; Li WB; Yang Z; Hoffman RM; Yu C Anticancer Res; 2019 Apr; 39(4):1689-1698. PubMed ID: 30952707 [TBL] [Abstract][Full Text] [Related]
7. 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]
8. Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis. Fang E; Zhang X Cancer Biomark; 2017 Dec; 21(1):373-381. PubMed ID: 29081411 [TBL] [Abstract][Full Text] [Related]
9. Prediction of Target Genes and Pathways Associated With Cetuximab Insensitivity in Colorectal Cancer. Yu C; Hong H; Lu J; Zhao X; Hu W; Zhang S; Zong Y; Mao Z; Li J; Wang M; Feng B; Sun J; Zheng M Technol Cancer Res Treat; 2018 Jan; 17():1533033818806905. PubMed ID: 30336768 [TBL] [Abstract][Full Text] [Related]
10. 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]
11. Identification of Hub Genes Associated with Tumor-Infiltrating Immune Cells and ECM Dynamics as the Potential Therapeutic Targets in Gastric Cancer through an Integrated Bioinformatic Analysis and Machine Learning Methods. Liu J; Cheng Z Comb Chem High Throughput Screen; 2023; 26(4):653-667. PubMed ID: 35996248 [TBL] [Abstract][Full Text] [Related]
12. 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]
13. Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer. Dong X; Dai H; Sun A; Yu Z; Du Y J Immunol Res; 2022; 2022():9529114. PubMed ID: 35935587 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. High-efficient Screening Method for Identification of Key Genes in Breast Cancer Through Microarray and Bioinformatics. Liu Z; Liang G; Tan L; Su AN; Jiang W; Gong C Anticancer Res; 2017 Aug; 37(8):4329-4335. PubMed ID: 28739725 [TBL] [Abstract][Full Text] [Related]
16. Screening and Survival Analysis of Hub Genes in Gastric Cancer Based on Bioinformatics. Zheng S; Yang L; Dai Y; Jiang L; Wei Y; Wen H; Xu Y J Comput Biol; 2019 Nov; 26(11):1316-1325. PubMed ID: 31233344 [No Abstract] [Full Text] [Related]
17. 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]
18. Bioinformatics-Based Identification of Methylated-Differentially Expressed Genes and Related Pathways in Gastric Cancer. Li H; Liu JW; Liu S; Yuan Y; Sun LP Dig Dis Sci; 2017 Nov; 62(11):3029-3039. PubMed ID: 28914394 [TBL] [Abstract][Full Text] [Related]
19. Identification and Analysis of Key Genes Driving Gastric Cancer Through Bioinformatics. Liu Z; Liu S; Guo J; Sun L; Wang S; Wang Y; Qiu W; Lv J Genet Test Mol Biomarkers; 2021 Jan; 25(1):1-11. PubMed ID: 33470887 [No Abstract] [Full Text] [Related]
20. Target gene screening and evaluation of prognostic values in non-small cell lung cancers by bioinformatics analysis. Piao J; Sun J; Yang Y; Jin T; Chen L; Lin Z Gene; 2018 Mar; 647():306-311. PubMed ID: 29305979 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]