The node-based overlap between this network and other networks is calculated as the Szymkiewicz-Simpson coefficient of their respective nodes. Up to the top 10 are shown below.
|Identification of a novel aspartic protease (Asp 2) as beta-secretase v1.0.0||20%|
|Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0||17%|
|Protein aggregation can inhibit clathrin-mediated endocytosis by chaperone competition v1.0.0||15%|
|Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0||12%|
|Pathological missorting of endogenous MAPT/Tau in neurons caused by failure of protein degradation systems v1.0.1||11%|
|Nicotinic α4β2 acetylcholine receptors and cognitive function in Parkinson's disease v1.0.0||11%|
|Abnormal Alzheimer-like phosphorylation of tau-protein by cyclin-dependent kinases cdk2 and cdk5 v1.0.0||10%|
|Molecular chaperones and proteostasis regulation during redox imbalance v1.0.0||9%|
|Tau Trimers Are the Minimal Propagation Unit Spontaneously Internalized to Seed Intracellular Aggregation v1.0.0||9%|
|Selective activation of α7 nicotinic acetylcholine receptor by PHA-543613 improves Aβ25-35-mediated cognitive deficits in mice v1.0.0||9%|
The greatest FImax was observed with Protandim at 135-fold, followed by bardoxolone methyl at 67-fold, dimethyl fumarate at 55-fold, and sulforaphane at 21-fold
When compared contemporaneously in the AREc32-based assay, FImax observed was in the order Protandim > bardoxolone methyl > dimethyl fumarate > sulforaphane.
A recent laboratory study of dimethyl fumarate found that the compound activates Nrf2 in primary astrocytes, but not in the C6 glioma-derived cell line (Wilms et al., 2010), demonstrating that different cells may respond quite differently to Nrf2 activators
BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.
If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.