ArticlePloS one2015
Predicting Abdominal Aortic Aneurysm Target Genes by Level-2 Protein-Protein Interaction.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 2 citations in OpenAlex.
- AAAKB: A manually curated database for tracking and predicting genes of Abdominal aortic aneurysm (AAA).PloS one · 2023Article
- Identification of key genes and pathways in abdominal aortic aneurysm by integrated bioinformatics analysis.The Journal of international medical research · 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
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abdominal aortic aneurysm (AAA) is frequently lethal and has no effective pharmaceutical treatment, posing a great threat to human health. Previous bioinformatics studies of the mechanisms underlying AAA relied largely on the detection of direct protein-protein interactions (level-1 PPI) between the products of reported AAA-related genes. Thus, some proteins not suspected to be directly linked to previously reported genes of pivotal importance to AAA might have been missed. In this study, we constructed an indirect protein-protein interaction (level-2 PPI) network based on common interacting proteins encoded by known AAA-related genes and successfully predicted previously unreported AAA-related genes using this network. We used four methods to test and verify the performance of this level-2 PPI network: cross validation, human AAA mRNA chip array comparison, literature mining, and verification in a mouse CaPO4 AAA model. We confirmed that the new level-2 PPI network is superior to the original level-1 PPI network and proved that the top 100 candidate genes predicted by the level-2 PPI network shared similar GO functions and KEGG pathways compared with positive genes.
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.