149 related articles for article (PubMed ID: 32382535)
21. 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]
22. Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis.
Li L; Lei Q; Zhang S; Kong L; Qin B
Oncol Rep; 2017 Nov; 38(5):2607-2618. PubMed ID: 28901457
[TBL] [Abstract][Full Text] [Related]
23. 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]
24. Identification of candidate aberrantly methylated and differentially expressed genes in Esophageal squamous cell carcinoma.
Han BA; Yang XP; Hosseini DK; Zhang P; Zhang Y; Yu JT; Chen S; Zhang F; Zhou T; Sun HY
Sci Rep; 2020 Jun; 10(1):9735. PubMed ID: 32546690
[TBL] [Abstract][Full Text] [Related]
25. Bioinformatic identification of candidate biomarkers and related transcription factors in nasopharyngeal carcinoma.
Ye Z; Wang F; Yan F; Wang L; Li B; Liu T; Hu F; Jiang M; Li W; Fu Z
World J Surg Oncol; 2019 Apr; 17(1):60. PubMed ID: 30935420
[TBL] [Abstract][Full Text] [Related]
26. Identification of Key Biomarkers and Potential Molecular Mechanisms in Renal Cell Carcinoma by Bioinformatics Analysis.
Li F; Guo P; Dong K; Guo P; Wang H; Lv X
J Comput Biol; 2019 Nov; 26(11):1278-1295. PubMed ID: 31233342
[No Abstract] [Full Text] [Related]
27. 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]
28. Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.
Chen L; Lu D; Sun K; Xu Y; Hu P; Li X; Xu F
Gene; 2019 Apr; 692():119-125. PubMed ID: 30654001
[TBL] [Abstract][Full Text] [Related]
29. Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma.
Zhou L; Tang H; Wang F; Chen L; Ou S; Wu T; Xu J; Guo K
Mol Med Rep; 2018 Nov; 18(5):4185-4196. PubMed ID: 30132538
[TBL] [Abstract][Full Text] [Related]
30. Screening and identification of potential biomarkers and therapeutic drugs in melanoma via integrated bioinformatics analysis.
Chen B; Sun D; Qin X; Gao XH
Invest New Drugs; 2021 Aug; 39(4):928-948. PubMed ID: 33501609
[TBL] [Abstract][Full Text] [Related]
31. 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]
32. Identification of aberrantly methylated differentially expressed genes in breast cancer by integrated bioinformatics analysis.
Yi L; Luo P; Zhang J
J Cell Biochem; 2019 Sep; 120(9):16229-16243. PubMed ID: 31081184
[TBL] [Abstract][Full Text] [Related]
33. Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis.
Zhang L; Lu D; Liu M; Zhang M; Peng Q
Mol Med Rep; 2019 Sep; 20(3):2316-2324. PubMed ID: 31322209
[TBL] [Abstract][Full Text] [Related]
34. Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis.
Zhou Z; Li Y; Hao H; Wang Y; Zhou Z; Wang Z; Chu X
Cell Transplant; 2019 Dec; 28(1_suppl):76S-86S. PubMed ID: 31822116
[TBL] [Abstract][Full Text] [Related]
35. Understanding the Molecular Genetics of Basal Cell Carcinoma.
Pellegrini C; Maturo MG; Di Nardo L; Ciciarelli V; Gutiérrez García-Rodrigo C; Fargnoli MC
Int J Mol Sci; 2017 Nov; 18(11):. PubMed ID: 29165358
[TBL] [Abstract][Full Text] [Related]
36. Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
Xu Y; Kong D; Li Z; Qian L; Li J; Zou C
PLoS One; 2021; 16(8):e0254868. PubMed ID: 34358255
[TBL] [Abstract][Full Text] [Related]
37. 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]
38. Detailed Analysis of Molecular Mechanisms in Primary and Metastatic Melanoma.
Xu Y; Mu Y; Wang L; Zhang X
J Comput Biol; 2020 Jan; 27(1):9-19. PubMed ID: 31424282
[TBL] [Abstract][Full Text] [Related]
39. Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer.
Zhang W; Zhang Q; Che L; Xie Z; Cai X; Gong L; Li Z; Liu D; Liu S
BMC Cancer; 2022 Mar; 22(1):299. PubMed ID: 35313857
[TBL] [Abstract][Full Text] [Related]
40. Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis.
Tang Y; Zhang Y; Hu X
Biomed Res Int; 2020; 2020():4251761. PubMed ID: 33376723
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
