Upload at 2019-02-27 16:11:59.490990
Rana Aldisi
CC BY 4.0
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
Number Edges
Number Components
Network Density
Average Degree
Number Citations
Number BEL Errors

Content Statistics

Network Overlap

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.

Network Overlap
M1 muscarinic acetylcholine receptor in Alzheimer’s disease v1.0.0 40%
Nicotinic acetylcholine receptor signalling: roles in Alzheimer's disease and amyloid neuroprotection. v1.0.0 40%
The Spleen Tyrosine Kinase (Syk) Regulates Alzheimer Amyloid-β Production and Tau Hyperphosphorylation* v1.0.0 30%
Nuclear receptors as therapeutic targets for Alzheimer's disease. v1.0.0 30%
The Ubiquitin Proteasome System in Neurodegenerative Diseases: Sometimes the Chicken, Sometimes the Egg v1.0.0 30%
Clearance systems in the brain-implications for Alzheimer disease. v1.0.1 30%
Clearance of Amyloid Beta and Tau in Alzheimer’s Disease:from Mechanisms to Therapy v1.0.1 30%
Anatabine lowers Alzheimer's Aβ production in vitro and in vivo v1.0.0 30%
Phytochemicals as inhibitors of NF-κB for treatment of Alzheimer’s disease v1.0.0 30%
Identification of a novel aspartic protease (Asp 2) as beta-secretase v1.0.0 30%

Sample Edges

Sample Nodes


In-Edges: 423 | Out-Edges: 245 | Children: 5 | Explore Neighborhood | Download JSON

a(CHEBI:"amyloid-beta polypeptide 40")

In-Edges: 23 | Out-Edges: 5 | Classes: 1 | Explore Neighborhood | Download JSON


In-Edges: 15 | Out-Edges: 1 | Explore Neighborhood | Download JSON


In-Edges: 12 | Out-Edges: 1 | Explore Neighborhood | Download JSON


In-Edges: 65 | Out-Edges: 39 | Explore Neighborhood | Download JSON


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.