ArticleFrontiers in physiology2016
Network Analysis-Based Approach for Exploring the Potential Diagnostic Biomarkers of Acute Myocardial Infarction.
Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 46 citations in OpenAlex.
- Bioinformatics and Experimental Validation of Diagnostic Marker Genes for Myocardial Infarction and Analysis of Their Immune Cell Infiltration.Biochemical genetics · 2026Article
- Deciphering the clinical implication of an obesity-related gene signature as the novel biomarker for acute myocardial infarction diagnosis.Scientific reports · 2025Article
- Identification of neutrophil extracellular traps-related genes for the diagnosis of acute myocardial infarction based on bioinformatics and experimental verification.Journal of inflammation (London, England) · 2025Article
- Comprehensive bioinformatics analytics andAging · 2024Article
- Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study.PloS one · 2024Article
- Integration of machine learning to identify diagnostic genes in leukocytes for acute myocardial infarction patients.Journal of translational medicine · 2023Article
- Integrative analysis of DNA methylation and gene expression reveals key molecular signatures in acute myocardial infarction.Clinical epigenetics · 2022Article
- Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- Machine learning-based integration develops biomarkers initial the crosstalk between inflammation and immune in acute myocardial infarction patients.Frontiers in cardiovascular medicine · 2022Article
- Construction of Novel Gene Signature-Based Predictive Model for the Diagnosis of Acute Myocardial Infarction by Combining Random Forest With Artificial Neural Network.Frontiers in cardiovascular medicine · 2022Article
- PRKAR1A and SDCBP Serve as Potential Predictors of Heart Failure Following Acute Myocardial Infarction.Frontiers in immunology · 2022Article
- Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- Screening for Regulatory Network of miRNA-Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study.International journal of general medicine · 2022Article
- Identification of monocyte-associated genes as predictive biomarkers of heart failure after acute myocardial infarction.BMC medical genomics · 2021Article
- Identification of Biomarkers Related to Immune Cell Infiltration with Gene Coexpression Network in Myocardial Infarction.Disease markers · 2021Article
- Identification of key gene modules and pathways of human platelet transcriptome in acute myocardial infarction patients through co-expression network.American journal of translational research · 2021Article
- Weighted gene co-expression network analysis identified underlying hub genes and mechanisms in the occurrence and development of viral myocarditis.Annals of translational medicine · 2020Article
- Identifying the pattern of immune related cells and genes in the peripheral blood of ischemic stroke.Journal of translational medicine · 2020Article
- A novel single-cell based method for breast cancer prognosis.PLoS computational biology · 2020Article
- Critical Roles of ELVOL4 and IL-33 in the Progression of Obesity-Related Cardiomyopathy via Integrated Bioinformatics Analysis.Frontiers in physiology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute myocardial infarction (AMI) is a severe cardiovascular disease that is a serious threat to human life. However, the specific diagnostic biomarkers have not been fully clarified and candidate regulatory targets for AMI have not been identified. In order to explore the potential diagnostic biomarkers and possible regulatory targets of AMI, we used a network analysis-based approach to analyze microarray expression profiling of peripheral blood in patients with AMI. The significant differentially-expressed genes (DEGs) were screened by Limma and constructed a gene function regulatory network (GO-Tree) to obtain the inherent affiliation of significant function terms. The pathway action network was constructed, and the signal transfer relationship between pathway terms was mined in order to investigate the impact of core pathway terms in AMI. Subsequently, constructed the transcription regulatory network of DEGs. Weighted gene co-expression network analysis (WGCNA) was employed to identify significantly altered gene modules and hub genes in two groups. Subsequently, the transcription regulation network of DEGs was constructed. We found that specific gene modules may provide a better insight into the potential diagnostic biomarkers of AMI. Our findings revealed and verified that
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.