ArticleJournal of proteomics and genomics research2017
Bioinformatic Analysis of Coronary Disease Associated SNPs and Genes to Identify Proteins Potentially Involved in the Pathogenesis of Atherosclerosis.
Article in Journal of proteomics and genomics research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Role of apolipoprotein C1 in lipoprotein metabolism, atherosclerosis and diabetes: a systematic review.Cardiovascular diabetology · 2022Pooled it
- Exploring the Potential of Calebin-A in Targeting Obesity-Related Genes and Pathways.Journal of cellular and molecular medicine · 2026Article
- Improving T2D machine learning-based prediction accuracy with SNPs and younger age.Computational and structural biotechnology journal · 2025Article
- SR-B1-/-ApoE-R61h/h Mice Mimic Human Coronary Heart Disease.Cardiovascular drugs and therapy · 2024Review
- PHACTR1 and APOC1 genetic variants are associated with multi-vessel coronary artery disease.Lipids in health and disease · 2024Article
- Effect of Calebin-A on Critical Genes Related to NAFLD: A Protein-Protein Interaction Network and Molecular Docking Study.Current genomics · 2024Article
- Identification and validation of hub genes involved in foam cell formation and atherosclerosis developmentPeerJ · 2023Article
- Cardiovascular Diseases in the Digital Health Era: A Translational Approach from the Lab to the Clinic.Biotech (Basel (Switzerland)) · 2022Review
- Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis.BMC cardiovascular disorders · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 8 institutions in 2 countries.
Funding
Abstract
Factors that contribute to the onset of atherosclerosis may be elucidated by bioinformatic techniques applied to multiple sources of genomic and proteomic data. The results of genome wide association studies, such as the CardioGramPlusC4D study, expression data, such as that available from expression quantitative trait loci (eQTL) databases, along with protein interaction and pathway data available in Ingenuity Pathway Analysis (IPA), constitute a substantial set of data amenable to bioinformatics analysis. This study used bioinformatic analyses of recent genome wide association data to identify a seed set of genes likely associated with atherosclerosis. The set was expanded to include protein interaction candidates to create a network of proteins possibly influencing the onset and progression of atherosclerosis. Local average connectivity (LAC), eigenvector centrality, and betweenness metrics were calculated for the interaction network to identify top gene and protein candidates for a better understanding of the atherosclerotic disease process. The top ranking genes included some known to be involved with cardiovascular disease (
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.