Upload at 2019-03-15 15:43:52.642589
Esther Wollert
CC BY 4.0
Copyright © 2019 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
Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0 50%
Tau Modifications v1.9.5 46%
Tau in physiology and pathology v1.0.0 34%
Alzheimer's disease pathological lesions activate the spleen tyrosine kinase. v1.0.0 29%
Alzheimer’s disease and the autophagic-lysosomal system v1.0.0 27%
Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0 25%
Abnormal Alzheimer-like phosphorylation of tau-protein by cyclin-dependent kinases cdk2 and cdk5 v1.0.0 25%
Upstream regulators and downstream effectors of NF-κBinAlzheimer's disease v1.0.0 24%
Protein phosphatase 2A dysfunction in Alzheimer’s disease v1.0.0 24%
Neuronal uptake and propagation of a rare phosphorylated high-molecular-weight tau derived from Alzheimer’s disease brain v1.0.1 24%

Sample Edges

a(CHEBI:"amyloid-beta") association bp(GO:"axonal transport") View Subject | View Object

The amount of Aβ produced could be altered by delayed axonal transport, as well as the precise species of metabolites of APPproduced— e.g., Aβ40 or 42, monomeric Aβ, or Aβ-oligomers or Aβ-derived diffusible ligands (ADDLs) (Lambert et al., 1998; Walsh et al., 2000). PubMed:12428809

a(HBP:"straight filaments") association path(MESH:"Alzheimer Disease") View Subject | View Object

For the sake of completeness, we also refer to tau- 3R transgenic mice that developed another type of pathology in the hippocampus, e.g., straight fila- ments formed in aged mice older than 18 mo (Ishi- hara, 2001b), which was proposed to be relevant for AD, given the age-dependence. PubMed:12428809

Sample Nodes


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

path(MESH:"Alzheimer Disease")

In-Edges: 536 | Out-Edges: 704 | Classes: 5 | Explore Neighborhood | Download JSON


In-Edges: 106 | Out-Edges: 69 | Explore Neighborhood | Download JSON


In-Edges: 477 | Out-Edges: 480 | Classes: 11 | Children: 27 | Explore Neighborhood | Download JSON

p(HGNC:MAPT, pmod(Ph))

In-Edges: 201 | Out-Edges: 71 | Classes: 1 | Children: 4 | 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.