Provenance

Upload
charles.hoyt@scai.fraunhofer.de at 2019-02-27 16:23:19.037692
Authors
Kristian Kolpeja
Contact
charles.hoyt@scai.fraunhofer.de
License
CC BY 4.0
Copyright
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
107
Number Edges
203
Number Components
5
Network Density
0.0178980779403985
Average Degree
1.89719626168224
Number Citations
1
Number BEL Errors
0

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
Tau Modifications v1.9.5 96%
Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0 50%
Tau Trimers Are the Minimal Propagation Unit Spontaneously Internalized to Seed Intracellular Aggregation v1.0.0 36%
Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0 33%
Extracellular Monomeric and Aggregated Tau Efficiently Enter Human Neurons through Overlapping but Distinct Pathways v1.0.1 26%
Alzheimer's disease pathological lesions activate the spleen tyrosine kinase. v1.0.0 24%
Tau in physiology and pathology v1.0.0 23%
Identification of the Tau phosphorylation pattern that drives its aggregation v1.0.0 23%
Pseudophosphorylation of tau at S422 enhances SDS-stable dimer formation and impairs both anterograde and retrograde fast axonal transport. v1.0.0 20%
Tau Antibody Targeting Pathological Species Blocks Neuronal Uptake and Interneuron Propagation of Tau in Vitro v1.0.0 18%

Sample Edges

Sample Nodes

a(CHEBI:"amyloid-beta")

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

a(CHEBI:sirolimus)

In-Edges: 8 | Out-Edges: 50 | Explore Neighborhood | Download JSON

p(HGNC:MAPT)

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

About

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.