ArticleGene regulation and systems biology2016
Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE
Article in Gene regulation and systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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Who cites it
4 citing papers in PubMed.
- Construction of a Suite of Computable Biological Network Models Focused on Mucociliary Clearance in the Respiratory Tract.Frontiers in genetics · 2019Article
- Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature.BMC bioinformatics · 2018Article
- Systems toxicology meta-analysis ofToxicology research · 2017Article
- Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.Healthcare (Basel, Switzerland) · 2017Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE
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