ArticlePloS one2023
AAAKB: A manually curated database for tracking and predicting genes of Abdominal aortic aneurysm (AAA).
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 2 citations in OpenAlex.
- Comprehensive evaluation of plasma biomarkers in patients with abdominal aortic aneurysm using high-throughput, label-free quantitative proteomic profiling.American journal of physiology. Heart and circulatory physiology · 2026Article
- The Inflammation-Thrombosis Genetic Axis in Abdominal Aortic Aneurysm: A Shared Roadmap to Precision Medicine.TH open : companion journal to thrombosis and haemostasis · 2026Review
- Graph Neural Networks Reveal Candidate Protein Biomarkers Underlying Abdominal Aortic Aneurysm Biology.Computational and structural biotechnology journal · 2026Article
- Understanding genomic medicine for thoracic aortic disease through the lens of induced pluripotent stem cells.Frontiers in cardiovascular medicine · 2024Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abdominal aortic aneurysm (AAA), an extremely dangerous vascular disease with high mortality, causes massive internal bleeding due to aneurysm rupture. To boost the research on AAA, efforts should be taken to organize and link the information about AAA-related genes and their functions. Currently, most researchers screen through genetic databases manually, which is cumbersome and time-consuming. Here, we developed "AAAKB" a manually curated knowledgebase containing genes, SNPs and pathways associated with AAA. In order to facilitate researchers to further explore the mechanism network of AAA, AAAKB provides predicted genes that are potentially associated with AAA. The prediction is based on the protein interaction information of genes collected in the database, and the random forest algorithm (RF) is used to build the prediction model. Some of these predicted genes are differentially expressed in patients with AAA, and some have been reported to play a role in other cardiovascular diseases, illustrating the utility of the knowledgebase in predicting novel genes. Also, AAAKB integrates a protein interaction visualization tool to quickly determine the shortest paths between target proteins. As the first knowledgebase to provide a comprehensive catalog of AAA-related genes, AAAKB will be an ideal research platform for AAA. Database URL: http://www.lqlgroup.cn:3838/AAAKB/.
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Registered trials
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