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10.1097/MD.0000000000007741

http://scihub22266oqcxt.onion/10.1097/MD.0000000000007741
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suck abstract from ncbi


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pmid29049183
      Medicine+(Baltimore) 2017 ; 96 (42 ): e7741
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  • Identifying key genes associated with acute myocardial infarction #MMPMID29049183
  • Cheng M ; An S ; Li J
  • Medicine (Baltimore) 2017[Oct]; 96 (42 ): e7741 PMID29049183 show ga
  • BACKGROUND: This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. METHODS: Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P?
  • |Cell Cycle Proteins/*genetics [MESH]
  • |Databases, Genetic [MESH]
  • |Down-Regulation/genetics [MESH]
  • |Forkhead Box Protein O3/*genetics [MESH]
  • |Gene Expression Profiling [MESH]
  • |Gene Expression Regulation [MESH]
  • |Gene Regulatory Networks/*genetics [MESH]
  • |Genetic Association Studies [MESH]
  • |Humans [MESH]
  • |MicroRNAs/metabolism [MESH]
  • |Myocardial Infarction/*genetics [MESH]
  • |Real-Time Polymerase Chain Reaction [MESH]
  • |Trans-Activators/*genetics [MESH]
  • |Transcription Factors/genetics [MESH]


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