113 related articles for article (PubMed ID: 27460729)
1. Bioinformatic analysis of RNA-seq data unveiled critical genes in rectal adenocarcinoma.
Zuo ZG; Zhang XF; Ye XZ; Zhou ZH; Wu XB; Ni SC; Song HY
Eur Rev Med Pharmacol Sci; 2016 Jul; 20(14):3017-25. PubMed ID: 27460729
[TBL] [Abstract][Full Text] [Related]
2. Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.
Xi WD; Liu YJ; Sun XB; Shan J; Yi L; Zhang TT
Eur Rev Med Pharmacol Sci; 2017 Jul; 21(13):3012-3020. PubMed ID: 28742206
[TBL] [Abstract][Full Text] [Related]
3. Key Genes in Stomach Adenocarcinoma Identified via Network Analysis of RNA-Seq Data.
Shen L; Zhao L; Tang J; Wang Z; Bai W; Zhang F; Wang S; Li W
Pathol Oncol Res; 2017 Oct; 23(4):745-752. PubMed ID: 28058586
[TBL] [Abstract][Full Text] [Related]
4. E2F, HSF2, and miR-26 in thyroid carcinoma: bioinformatic analysis of RNA-sequencing data.
Lu JC; Zhang YP
Genet Mol Res; 2016 Mar; 15(1):15017576. PubMed ID: 26985959
[TBL] [Abstract][Full Text] [Related]
5. Bioinformatics analysis of RNA sequencing data reveals multiple key genes in uterine corpus endometrial carcinoma.
Shen L; Liu M; Liu W; Cui J; Li C
Oncol Lett; 2018 Jan; 15(1):205-212. PubMed ID: 29387216
[TBL] [Abstract][Full Text] [Related]
6. Identification of hub genes and potential molecular mechanisms related to radiotherapy sensitivity in rectal cancer based on multiple datasets.
Zhao P; Zhen H; Zhao H; Huang Y; Cao B
J Transl Med; 2023 Mar; 21(1):176. PubMed ID: 36879254
[TBL] [Abstract][Full Text] [Related]
7. Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis.
Mou T; Zhu D; Wei X; Li T; Zheng D; Pu J; Guo Z; Wu Z
World J Surg Oncol; 2017 Mar; 15(1):63. PubMed ID: 28302149
[TBL] [Abstract][Full Text] [Related]
8. Gene expression profile identifies potential biomarkers for human intervertebral disc degeneration.
Guo W; Zhang B; Li Y; Duan HQ; Sun C; Xu YQ; Feng SQ
Mol Med Rep; 2017 Dec; 16(6):8665-8672. PubMed ID: 29039500
[TBL] [Abstract][Full Text] [Related]
9. Bioinformatics analyses of the differences between lung adenocarcinoma and squamous cell carcinoma using The Cancer Genome Atlas expression data.
Sun F; Yang X; Jin Y; Chen L; Wang L; Shi M; Zhan C; Shi Y; Wang Q
Mol Med Rep; 2017 Jul; 16(1):609-616. PubMed ID: 28560415
[TBL] [Abstract][Full Text] [Related]
10. In silico analysis of the molecular mechanism of postmenopausal osteoporosis.
Liu Y; Wang Y; Yang N; Wu S; Lv Y; Xu L
Mol Med Rep; 2015 Nov; 12(5):6584-90. PubMed ID: 26329309
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Identification of key genes in endometrioid endometrial adenocarcinoma via TCGA database.
Liu Y; Nan F; Lu K; Wang Y; Liu Y; Wei S; Wu R; Wang Y
Cancer Biomark; 2017 Dec; 21(1):11-21. PubMed ID: 29060924
[TBL] [Abstract][Full Text] [Related]
13. Screening of Critical Genes and MicroRNAs in Blood Samples of Patients with Ruptured Intracranial Aneurysms by Bioinformatic Analysis of Gene Expression Data.
Bo L; Wei B; Wang Z; Kong D; Gao Z; Miao Z
Med Sci Monit; 2017 Sep; 23():4518-4525. PubMed ID: 28930970
[TBL] [Abstract][Full Text] [Related]
14. Identification of differentially expressed genes between lung adenocarcinoma and lung squamous cell carcinoma by gene expression profiling.
Lu C; Chen H; Shan Z; Yang L
Mol Med Rep; 2016 Aug; 14(2):1483-90. PubMed ID: 27356570
[TBL] [Abstract][Full Text] [Related]
15. Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis.
He H; Mao L; Xu P; Xi Y; Xu N; Xue M; Yu J; Ye X
Gene; 2014 Jan; 533(2):515-9. PubMed ID: 24055420
[TBL] [Abstract][Full Text] [Related]
16. Critical genes of hepatocellular carcinoma revealed by network and module analysis of RNA-seq data.
Yang MR; Zhang Y; Wu XX; Chen W
Eur Rev Med Pharmacol Sci; 2016 Oct; 20(20):4248-4256. PubMed ID: 27831650
[TBL] [Abstract][Full Text] [Related]
17. Bioinformatic Analysis of Genes and MicroRNAs Associated With Atrioventricular Septal Defect in Down Syndrome Patients.
Wang L; Li Z; Song X; Liu L; Su G; Cui Y
Int Heart J; 2016 Jul; 57(4):490-5. PubMed ID: 27396555
[TBL] [Abstract][Full Text] [Related]
18. Gene expression profiling via bioinformatics analysis reveals biomarkers in laryngeal squamous cell carcinoma.
Guan GF; Zheng Y; Wen LJ; Zhang DJ; Yu DJ; Lu YQ; Zhao Y; Zhang H
Mol Med Rep; 2015 Aug; 12(2):2457-64. PubMed ID: 25936657
[TBL] [Abstract][Full Text] [Related]
19. Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis.
Luo S; Cao N; Tang Y; Gu W
PLoS One; 2017; 12(6):e0178549. PubMed ID: 28594854
[TBL] [Abstract][Full Text] [Related]
20. Prognostic targets recognition of rectal adenocarcinoma based on transcriptomics.
Yi X; Zhou Y; Zheng H; Wang L; Xu T; Fu C; Su X
Medicine (Baltimore); 2021 Aug; 100(32):e25909. PubMed ID: 34397867
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]