123 related articles for article (PubMed ID: 37949208)
1. Network based approach to identify interactions between Type 2 diabetes and cancer comorbidities.
Nayan SI; Rahman MH; Hasan MM; Raj SMRH; Almoyad MAA; Liò P; Moni MA
Life Sci; 2023 Dec; 335():122244. PubMed ID: 37949208
[TBL] [Abstract][Full Text] [Related]
2. A Network-Based Bioinformatics Approach to Identify Molecular Biomarkers for Type 2 Diabetes that Are Linked to the Progression of Neurological Diseases.
Rahman MH; Peng S; Hu X; Chen C; Rahman MR; Uddin S; Quinn JMW; Moni MA
Int J Environ Res Public Health; 2020 Feb; 17(3):. PubMed ID: 32041280
[TBL] [Abstract][Full Text] [Related]
3. Statistical Bioinformatics to Uncover the Underlying Biological Mechanisms That Linked Smoking with Type 2 Diabetes Patients Using Transcritpomic and GWAS Analysis.
Ripon Rouf ASM; Amin MA; Islam MK; Haque F; Ahmed KR; Rahman MA; Islam MZ; Kim B
Molecules; 2022 Jul; 27(14):. PubMed ID: 35889263
[TBL] [Abstract][Full Text] [Related]
4. Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis.
Huang X; Zhang KJ; Jiang JJ; Jiang SY; Lin JB; Lou YJ
Front Endocrinol (Lausanne); 2022; 13():801260. PubMed ID: 35242109
[TBL] [Abstract][Full Text] [Related]
5. Expression profile of mitrogen-activated protein kinase (MAPK) signaling genes in the skeletal muscle & liver of rat with type 2 diabetes: role in disease pathology.
Tang X; Deng L; Xiong H; Li G; Lin J; Liu S; Xie J; Liu J; Kong F; Tu G; Peng H; Liang S
Indian J Med Res; 2014 Dec; 140(6):744-55. PubMed ID: 25758573
[TBL] [Abstract][Full Text] [Related]
6. Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer.
Yang D; He Y; Wu B; Deng Y; Wang N; Li M; Liu Y
J Ovarian Res; 2020 Jan; 13(1):10. PubMed ID: 31987036
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Identification of Hepatocellular Carcinoma-Related Potential Genes and Pathways Through Bioinformatic-Based Analyses.
Wan Z; Zhang X; Luo Y; Zhao B
Genet Test Mol Biomarkers; 2019 Nov; 23(11):766-777. PubMed ID: 31633428
[No Abstract] [Full Text] [Related]
9. Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.
Gao ZY; Su LC; Wu QC; Sheng JE; Wang YL; Dai YF; Chen AP; He SS; Huang X; Yan GQ
Clin Rheumatol; 2022 Feb; 41(2):437-452. PubMed ID: 34553293
[TBL] [Abstract][Full Text] [Related]
10. Analysis of potential key genes in very early hepatocellular carcinoma.
Wu M; Liu Z; Li X; Zhang A; Lin D; Li N
World J Surg Oncol; 2019 May; 17(1):77. PubMed ID: 31043166
[TBL] [Abstract][Full Text] [Related]
11. Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis.
Wu M; Liu Z; Zhang A; Li N
Medicine (Baltimore); 2019 Feb; 98(5):e14287. PubMed ID: 30702595
[TBL] [Abstract][Full Text] [Related]
12. Identification of crucial hub genes and potential molecular mechanisms in breast cancer by integrated bioinformatics analysis and experimental validation.
Yadav DK; Sharma A; Dube P; Shaikh S; Vaghasia H; Rawal RM
Comput Biol Med; 2022 Oct; 149():106036. PubMed ID: 36096037
[TBL] [Abstract][Full Text] [Related]
13. Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.
Vastrad B; Vastrad C; Tengli A; Iliger S
Arch Gynecol Obstet; 2018 Jan; 297(1):161-183. PubMed ID: 29063236
[TBL] [Abstract][Full Text] [Related]
14. 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. PubMed ID: 30525236
[TBL] [Abstract][Full Text] [Related]
15. Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in mice.
Zhao J; He K; Du H; Wei G; Wen Y; Wang J; Zhou X; Wang J
PeerJ; 2022; 10():e13932. PubMed ID: 36157062
[TBL] [Abstract][Full Text] [Related]
16. Combining bioinformatics, network pharmacology and artificial intelligence to predict the mechanism of celastrol in the treatment of type 2 diabetes.
Wu M; Zhang Y
Front Endocrinol (Lausanne); 2022; 13():1030278. PubMed ID: 36339449
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer.
Alwadi D; Felty Q; Yoo C; Roy D; Deoraj A
Int J Mol Sci; 2023 Feb; 24(4):. PubMed ID: 36834602
[TBL] [Abstract][Full Text] [Related]
19. Blood transcriptome analysis revealed the crosstalk between COVID-19 and HIV.
Yan C; Niu Y; Wang X
Front Immunol; 2022; 13():1008653. PubMed ID: 36389792
[TBL] [Abstract][Full Text] [Related]
20. Identification of key candidate genes and biological pathways in neuropathic pain.
Cui CY; Liu X; Peng MH; Liu Q; Zhang Y
Comput Biol Med; 2022 Nov; 150():106135. PubMed ID: 36166989
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]