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Items: 1 to 20 of 97

1.

Analysis of risk factors for colon cancer progression.

Yang Z, Chen Y, Wu D, Min Z, Quan Y.

Onco Targets Ther. 2019 May 22;12:3991-4000. doi: 10.2147/OTT.S207390. eCollection 2019.

2.

Exploring prognostic genes in ovarian cancer stage-related coexpression network modules.

Yang L, Jing J, Sun L, Yue Y.

Medicine (Baltimore). 2018 Aug;97(34):e11895. doi: 10.1097/MD.0000000000011895.

3.

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. doi: 10.1007/s12032-017-0963-9. Epub 2017 Apr 21.

4.

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. doi: 10.1016/j.prp.2019.02.012. Epub 2019 Feb 28.

PMID:
30975489
5.

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 24;9(1):7827. doi: 10.1038/s41598-019-43924-x.

6.

Eleven genes associated with progression and prognosis of endometrial cancer (EC) identified by comprehensive bioinformatics analysis.

Liu J, Zhou S, Li S, Jiang Y, Wan Y, Ma X, Cheng W.

Cancer Cell Int. 2019 May 20;19:136. doi: 10.1186/s12935-019-0859-1. eCollection 2019.

7.

Identification of molecular marker associated with ovarian cancer prognosis using bioinformatics analysis and experiments.

Zheng MJ, Li X, Hu YX, Dong H, Gou R, Nie X, Liu Q, Ying-Ying H, Liu JJ, Lin B.

J Cell Physiol. 2019 Jul;234(7):11023-11036. doi: 10.1002/jcp.27926. Epub 2019 Jan 11.

PMID:
30633343
8.

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis.

Yang X, Zhu S, Li L, Zhang L, Xian S, Wang Y, Cheng Y.

Onco Targets Ther. 2018 Mar 15;11:1457-1474. doi: 10.2147/OTT.S152238. eCollection 2018.

9.

Identification of core genes and outcomes in hepatocellular carcinoma by bioinformatics analysis.

Shen S, Kong J, Qiu Y, Yang X, Wang W, Yan L.

J Cell Biochem. 2019 Jun;120(6):10069-10081. doi: 10.1002/jcb.28290. Epub 2018 Dec 7.

PMID:
30525236
10.

Identification of key pathways and genes in endometrial cancer using bioinformatics analyses.

Liu Y, Hua T, Chi S, Wang H.

Oncol Lett. 2019 Jan;17(1):897-906. doi: 10.3892/ol.2018.9667. Epub 2018 Nov 5.

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 31;24:6059-6069. doi: 10.12659/MSM.910106.

12.

Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis.

He F, Ai B, Tian L.

Biomed Rep. 2018 Oct;9(4):305-312. doi: 10.3892/br.2018.1134. Epub 2018 Jul 25.

13.

Biomarker identification and trans-regulatory network analyses in esophageal adenocarcinoma and Barrett's esophagus.

Lv J, Guo L, Wang JH, Yan YZ, Zhang J, Wang YY, Yu Y, Huang YF, Zhao HP.

World J Gastroenterol. 2019 Jan 14;25(2):233-244. doi: 10.3748/wjg.v25.i2.233.

14.

Identification of hub genes and outcome in colon cancer based on bioinformatics analysis.

Yang W, Ma J, Zhou W, Li Z, Zhou X, Cao B, Zhang Y, Liu J, Yang Z, Zhang H, Zhao Q, Hong L, Fan D.

Cancer Manag Res. 2018 Dec 27;11:323-338. doi: 10.2147/CMAR.S173240. eCollection 2019.

15.

Combined analysis and validation for DNA methylation and gene expression profiles associated with prostate cancer.

Tong Y, Song Y, Deng S.

Cancer Cell Int. 2019 Mar 4;19:50. doi: 10.1186/s12935-019-0753-x. eCollection 2019.

16.

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.

PMID:
28739725
17.
18.

Identiļ¬cation of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis.

Wen P, Chidanguro T, Shi Z, Gu H, Wang N, Wang T, Li Y, Gao J.

Mol Med Rep. 2018 Aug;18(2):1538-1550. doi: 10.3892/mmr.2018.9095. Epub 2018 May 29.

19.

Identification and functional analysis of differentially expressed genes associated with cerebral ischemia/reperfusion injury through bioinformatics methods.

Shao X, Bao W, Hong X, Jiang H, Yu Z.

Mol Med Rep. 2018 Aug;18(2):1513-1523. doi: 10.3892/mmr.2018.9135. Epub 2018 Jun 6.

20.

Identification of key pathways and genes in the progression of cervical cancer using bioinformatics analysis.

Wu K, Yi Y, Liu F, Wu W, Chen Y, Zhang W.

Oncol Lett. 2018 Jul;16(1):1003-1009. doi: 10.3892/ol.2018.8768. Epub 2018 May 22.

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