Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Identifying key genes associated with acute myocardial infarction

1 Oct 2017

Abstract excerpt

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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cardiac Fibrosis and Remodeling
Share to FOXO transcription factor regulation
Share to Signaling Pathways in Disease

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Source

Identifiers

PMID: 29049183
DOI: 10.1097/md.0000000000007741

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 20 Oct 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying key genes associated with acute myocardial infarctionPMID 29049183Read ↗

Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome AnalysisSemantic proximity Read ↗

Integrated RNA gene expression analysis identified potential immune-related biomarkers and RNA regulatory pathways of acute myocardial infarctionSemantic proximity Read ↗

Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction.Semantic proximity Read ↗

Identification and analysis of key genes associated with acute myocardial infarction by integrated bioinformatics methodsSemantic proximity Read ↗

Genes associated with inflammation and the cell cycle may serve as biomarkers for the diagnosis and prognosis of acute myocardial infarction in a Chinese populationSemantic proximity Read ↗

Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics AnalysisSemantic proximity Read ↗

Identification of Key Genes and Signaling Pathways Involved in Acute Myocardial Infarction and Potential Biomarkers of Its Consequent Heart Failure Based On Bioinformatics AnalysisSemantic proximity Read ↗

Potential Biomarkers of Acute Myocardial Infarction Based on Co-Expression Network AnalysisSemantic proximity Read ↗

Identification and validation of mitochondrial dynamics-related genes in patients with acute myocardial infarction-a bioinformatics analysisSemantic proximity Read ↗

Biomarkers identification for acute myocardial infarction detection via weighted gene co-expression network analysisSemantic proximity Read ↗

Identification of Key Genes as Early Warning Signals of Acute Myocardial Infarction Based on Weighted Gene Correlation Network Analysis and Dynamic Network Biomarker AlgorithmSemantic proximity Read ↗

SCD leads to the development and progression of acute myocardial infarction through the AMPK signaling pathwaySemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.