The Identification of Key Genes and Biological Pathways in Cardiac Arrest by Integrated Bioinformatics and Next Generation Sequencing Data Analysis DOI Open Access
Basavaraj Vastrad, Chanabasayya Vastrad

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 19, 2024

Abstract Cardiac arrest (CA) is a common cause of death world wide. The disease has lacks effective treatment. Efforts have been made to elucidate the molecular pathogenesis CA, but mechanisms remain elusive. To identify key genes and pathways in next generation sequencing (NGS) GSE200117 dataset was downloaded from Gene Expression Omnibus (GEO) database. DESeq2 tool used recognize differentially expressed (DEGs). ontology (GO) REACTOME pathway enrichment analyses were performed analyze DEGs associated signal g:Profiler IID database construct protein-protein interaction (PPI) network, modules analysis using Cytoscape. A miRNA-hub gene regulatory network TF-hub then constructed screen miRNAs, TFs hub by miRNet NetworkAnalyst Cityscape software. Receiver operating characteristic curve (ROC) verified genes. In total, 844 identified, comprising 414 up regulated 430 down GO indicated that for CA mainly enriched organonitrogen compound metabolic process, response stimulus, translation immune system. Ten (up-regulated: HSPA8, HOXA1, INCA1 TP53; down-regulated: HSPB1, LMNA, SNCA, ADAMTSL4 PDLIM7) screened. We also predicted miRNAs (hsa-mir-1914-5p hsa-mir-598-3p) (JUN PRRX2) targeting This study uses series bioinformatics technologies obtain hug genes, TFs, related CA. These results provide us with new ideas finding biomarkers treatment methods

Language: Английский

The Identification of Key Genes and Biological Pathways in Cardiac Arrest by Integrated Bioinformatics and Next Generation Sequencing Data Analysis DOI Open Access
Basavaraj Vastrad, Chanabasayya Vastrad

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 19, 2024

Abstract Cardiac arrest (CA) is a common cause of death world wide. The disease has lacks effective treatment. Efforts have been made to elucidate the molecular pathogenesis CA, but mechanisms remain elusive. To identify key genes and pathways in next generation sequencing (NGS) GSE200117 dataset was downloaded from Gene Expression Omnibus (GEO) database. DESeq2 tool used recognize differentially expressed (DEGs). ontology (GO) REACTOME pathway enrichment analyses were performed analyze DEGs associated signal g:Profiler IID database construct protein-protein interaction (PPI) network, modules analysis using Cytoscape. A miRNA-hub gene regulatory network TF-hub then constructed screen miRNAs, TFs hub by miRNet NetworkAnalyst Cityscape software. Receiver operating characteristic curve (ROC) verified genes. In total, 844 identified, comprising 414 up regulated 430 down GO indicated that for CA mainly enriched organonitrogen compound metabolic process, response stimulus, translation immune system. Ten (up-regulated: HSPA8, HOXA1, INCA1 TP53; down-regulated: HSPB1, LMNA, SNCA, ADAMTSL4 PDLIM7) screened. We also predicted miRNAs (hsa-mir-1914-5p hsa-mir-598-3p) (JUN PRRX2) targeting This study uses series bioinformatics technologies obtain hug genes, TFs, related CA. These results provide us with new ideas finding biomarkers treatment methods

Language: Английский

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