124 related articles for article (PubMed ID: 38376276)
1. Integrated bioinformatics approach to unwind key genes and pathways involved in colorectal cancer.
Mobeen SA; Saxena P; Jain AK; Deval R; Riazunnisa K; Pradhan D
J Cancer Res Ther; 2023 Oct; 19(7):1766-1774. PubMed ID: 38376276
[TBL] [Abstract][Full Text] [Related]
2. Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments.
Zhang T; Guo J; Gu J; Wang Z; Wang G; Li H; Wang J
Oncol Rep; 2019 Jan; 41(1):279-291. PubMed ID: 30542696
[TBL] [Abstract][Full Text] [Related]
3. Identification of hub genes and pathways in lung metastatic colorectal cancer.
Dai W; Guo C; Wang Y; Li Y; Xie R; Wu J; Yao B; Xie D; He L; Li Y; Huang H; Wang Y; Liu S
BMC Cancer; 2023 Apr; 23(1):323. PubMed ID: 37024866
[TBL] [Abstract][Full Text] [Related]
4. Investigating potential molecular mechanisms of serum exosomal miRNAs in colorectal cancer based on bioinformatics analysis.
Wang H; Chen X; Bao L; Zhang X
Medicine (Baltimore); 2020 Sep; 99(37):e22199. PubMed ID: 32925795
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis.
Dai GP; Wang LP; Wen YQ; Ren XQ; Zuo SG
Oncol Lett; 2020 Jan; 19(1):388-398. PubMed ID: 31897151
[TBL] [Abstract][Full Text] [Related]
7. Bioinformatics-based identification of key genes and pathways associated with colorectal cancer diagnosis, treatment, and prognosis.
Wang C; Zhang L
Medicine (Baltimore); 2022 Sep; 101(37):e30619. PubMed ID: 36123948
[TBL] [Abstract][Full Text] [Related]
8. Identification of Hub Genes in Different Stages of Colorectal Cancer through an Integrated Bioinformatics Approach.
Patil AR; Leung MY; Roy S
Int J Environ Res Public Health; 2021 May; 18(11):. PubMed ID: 34070979
[TBL] [Abstract][Full Text] [Related]
9. Identification of key pathways and genes in colorectal cancer using bioinformatics analysis.
Liang B; Li C; Zhao J
Med Oncol; 2016 Oct; 33(10):111. PubMed ID: 27581154
[TBL] [Abstract][Full Text] [Related]
10. Identification of potential therapeutic targets associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.
Sharma A; Yadav D; Rao P; Sinha S; Goswami D; Rawal RM; Shrivastava N
Comput Biol Med; 2022 Jul; 146():105688. PubMed ID: 35680454
[TBL] [Abstract][Full Text] [Related]
11. Identification and Interaction Analysis of Molecular Markers in Colorectal Cancer by Integrated Bioinformatics Analysis.
Han B; Feng D; Yu X; Zhang Y; Liu Y; Zhou L
Med Sci Monit; 2018 Aug; 24():6059-6069. PubMed ID: 30168505
[TBL] [Abstract][Full Text] [Related]
12. Delineating the underlying molecular mechanisms and key genes involved in metastasis of colorectal cancer via bioinformatics analysis.
Qi C; Chen Y; Zhou Y; Huang X; Li G; Zeng J; Ruan Z; Xie X; Zhang J
Oncol Rep; 2018 May; 39(5):2297-2305. PubMed ID: 29517105
[TBL] [Abstract][Full Text] [Related]
13. Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis.
Lv J; Li L
Biomed Res Int; 2019; 2019():1545680. PubMed ID: 31781593
[TBL] [Abstract][Full Text] [Related]
14. Common gene signatures and key pathways in hypopharyngeal and esophageal squamous cell carcinoma: Evidence from bioinformatic analysis.
Zhou R; Liu D; Zhu J; Zhang T
Medicine (Baltimore); 2020 Oct; 99(42):e22434. PubMed ID: 33080677
[TBL] [Abstract][Full Text] [Related]
15. Complement C5 is a novel biomarker for liver metastasis of colorectal cancer.
Chang H; Jin L; Xie P; Zhang B; Yu M; Li H; Liu S; Yan J; Zhou B; Li X; Xu Y; Xiao Y; Ye Q; Guo L
J Gastrointest Oncol; 2022 Oct; 13(5):2351-2365. PubMed ID: 36388659
[TBL] [Abstract][Full Text] [Related]
16. CDK1 and CDC20 overexpression in patients with colorectal cancer are associated with poor prognosis: evidence from integrated bioinformatics analysis.
Li J; Wang Y; Wang X; Yang Q
World J Surg Oncol; 2020 Mar; 18(1):50. PubMed ID: 32127012
[TBL] [Abstract][Full Text] [Related]
17. Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis.
Yu C; Chen F; Jiang J; Zhang H; Zhou M
Mol Med Rep; 2019 Aug; 20(2):1259-1269. PubMed ID: 31173250
[TBL] [Abstract][Full Text] [Related]
18. Identification and verification of key cancer genes associated with prognosis of colorectal cancer based on bioinformatics analysis.
Qin Y; Chen L; Chen L
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2021 Oct; 46(10):1063-1070. PubMed ID: 34911835
[TBL] [Abstract][Full Text] [Related]
19. Bioinformatic Identification of Hub Genes and Analysis of Prognostic Values in Colorectal Cancer.
Lei X; Jing J; Zhang M; Guan B; Dong Z; Wang C
Nutr Cancer; 2021; 73(11-12):2568-2578. PubMed ID: 33153324
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]