269 related articles for article (PubMed ID: 24504536)
1. Screening of hub genes and pathways in colorectal cancer with microarray technology.
Wang Y; Zheng T
Pathol Oncol Res; 2014 Jul; 20(3):611-8. PubMed ID: 24504536
[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. 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]
4. Protein-protein interaction networks and modules analysis for colorectal cancer and serrated adenocarcinoma.
Yu H; Ye L; Wang J; Jin L; Lv Y; Yu M
J Cancer Res Ther; 2015; 11(4):846-51. PubMed ID: 26881529
[TBL] [Abstract][Full Text] [Related]
5. Employing bioinformatics analysis to identify hub genes and microRNAs involved in colorectal cancer.
Ebadfardzadeh J; Kazemi M; Aghazadeh A; Rezaei M; Shirvaliloo M; Sheervalilou R
Med Oncol; 2021 Aug; 38(9):114. PubMed ID: 34390411
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Analysis of key genes and pathways associated with colorectal cancer with microarray technology.
Liu YJ; Zhang S; Hou K; Li YT; Liu Z; Ren HL; Luo D; Li SH
Asian Pac J Cancer Prev; 2013; 14(3):1819-23. PubMed ID: 23679280
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. 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]
12. Identification of candidate biomarkers and therapeutic drugs of colorectal cancer by integrated bioinformatics analysis.
Zheng Z; Xie J; Xiong L; Gao M; Qin L; Dai C; Liang Z; Wang Y; Xue J; Wang Q; Wang W; Li X
Med Oncol; 2020 Oct; 37(11):104. PubMed ID: 33078282
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning.
Hammad A; Elshaer M; Tang X
Math Biosci Eng; 2021 Oct; 18(6):8997-9015. PubMed ID: 34814332
[TBL] [Abstract][Full Text] [Related]
15. Identification of Potential Key Genes and Pathways in Early-Onset Colorectal Cancer Through Bioinformatics Analysis.
Zhao B; Baloch Z; Ma Y; Wan Z; Huo Y; Li F; Zhao Y
Cancer Control; 2019; 26(1):1073274819831260. PubMed ID: 30786729
[TBL] [Abstract][Full Text] [Related]
16. Identification of key genes in colorectal cancer using random walk with restart.
Cui X; Shen K; Xie Z; Liu T; Zhang H
Mol Med Rep; 2017 Feb; 15(2):867-872. PubMed ID: 28000901
[TBL] [Abstract][Full Text] [Related]
17. Exploration of molecular mechanisms of diffuse large B-cell lymphoma development using a microarray.
Zhang ZX; Shen CF; Zou WH; Shou LH; Zhang HY; Jin WJ
Asian Pac J Cancer Prev; 2013; 14(3):1731-5. PubMed ID: 23679265
[TBL] [Abstract][Full Text] [Related]
18. Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data.
Vastrad B; Vastrad C; Godavarthi A; Chandrashekar R
Med Oncol; 2017 Sep; 34(11):182. PubMed ID: 28952134
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal Cancer.
Liu X; Bing Z; Wu J; Zhang J; Zhou W; Ni M; Meng Z; Liu S; Tian J; Zhang X; Li Y; Jia S; Guo S
Med Sci Monit; 2020 Jan; 26():e918906. PubMed ID: 31893510
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
