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Journal Abstract Search
345 related items for PubMed ID: 26208504
1. Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease. Zhang Y, Liu D, Wang L, Wang S, Yu X, Dai E, Liu X, Luo S, Jiang W. J Mol Med (Berl); 2015 Dec; 93(12):1381-90. PubMed ID: 26208504 [Abstract] [Full Text] [Related]
2. Systems biology approach identifies key regulators and the interplay between miRNAs and transcription factors for pathological cardiac hypertrophy. Recamonde-Mendoza M, Werhli AV, Biolo A. Gene; 2019 May 25; 698():157-169. PubMed ID: 30844478 [Abstract] [Full Text] [Related]
3. Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci. Zhao Y, Chen J, Freudenberg JM, Meng Q, Rajpal DK, Yang X. Arterioscler Thromb Vasc Biol; 2016 May 25; 36(5):928-41. PubMed ID: 26966275 [Abstract] [Full Text] [Related]
4. Integrated microRNA‑gene analysis of coronary artery disease based on miRNA and gene expression profiles. Xu X, Li H. Mol Med Rep; 2016 Apr 25; 13(4):3063-73. PubMed ID: 26936111 [Abstract] [Full Text] [Related]
5. Identification of key genes and crucial modules associated with coronary artery disease by bioinformatics analysis. Zhang X, Cheng X, Liu H, Zheng C, Rao K, Fang Y, Zhou H, Xiong S. Int J Mol Med; 2014 Sep 25; 34(3):863-9. PubMed ID: 24969630 [Abstract] [Full Text] [Related]
6. Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis. Song Z, Zhang C, He L, Sui Y, Lin X, Pan J. Biochem Biophys Res Commun; 2018 Jun 12; 500(4):902-906. PubMed ID: 29709470 [Abstract] [Full Text] [Related]
7. Integrated analyses to reconstruct microRNA-mediated regulatory networks in mouse liver using high-throughput profiling. Hsu SD, Huang HY, Chou CH, Sun YM, Hsu MT, Tsou AP. BMC Genomics; 2015 Jun 12; 16 Suppl 2(Suppl 2):S12. PubMed ID: 25707768 [Abstract] [Full Text] [Related]
8. BMRF-MI: integrative identification of protein interaction network by modeling the gene dependency. Shi X, Wang X, Shajahan A, Hilakivi-Clarke L, Clarke R, Xuan J. BMC Genomics; 2015 Jun 12; 16 Suppl 7(Suppl 7):S10. PubMed ID: 26099273 [Abstract] [Full Text] [Related]
10. Identification of active miRNA and transcription factor regulatory pathways in human obesity-related inflammation. Zhang XM, Guo L, Chi MH, Sun HM, Chen XW. BMC Bioinformatics; 2015 Mar 07; 16():76. PubMed ID: 25887648 [Abstract] [Full Text] [Related]
11. Identification of key regulators of pancreatic cancer progression through multidimensional systems-level analysis. Rajamani D, Bhasin MK. Genome Med; 2016 May 03; 8(1):38. PubMed ID: 27137215 [Abstract] [Full Text] [Related]
12. Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease. Liu J, Jing L, Tu X. BMC Cardiovasc Disord; 2016 Mar 05; 16():54. PubMed ID: 26944061 [Abstract] [Full Text] [Related]
17. Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data. Zhao X, Luan YZ, Zuo X, Chen YD, Qin J, Jin L, Tan Y, Lin M, Zhang N, Liang Y, Rao SQ. Genomics Proteomics Bioinformatics; 2016 Dec 05; 14(6):349-356. PubMed ID: 27965104 [Abstract] [Full Text] [Related]
18. Network analysis of inflammatory genes and their transcriptional regulators in coronary artery disease. Nair J, Ghatge M, Kakkar VV, Shanker J. PLoS One; 2014 Dec 05; 9(4):e94328. PubMed ID: 24736319 [Abstract] [Full Text] [Related]
19. Combination of microRNA expression profiling with genome-wide SNP genotyping to construct a coronary artery disease-related miRNA-miRNA synergistic network. Hua L, Xia H, Zhou P, Li D, Li L. Biosci Trends; 2014 Dec 05; 8(6):297-307. PubMed ID: 25641175 [Abstract] [Full Text] [Related]
20. Identification of susceptibility modules for coronary artery disease using a genome wide integrated network analysis. Duan S, Luo X, Dong C. Gene; 2013 Dec 01; 531(2):347-54. PubMed ID: 23994195 [Abstract] [Full Text] [Related] Page: [Next] [New Search]