287 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]
