Provenance

Upload
charles.hoyt@scai.fraunhofer.de at 2019-03-15 15:43:54.024418
Authors
Sandra Spalek
Contact
charles.hoyt@scai.fraunhofer.de
License
CC BY 4.0
Copyright
Copyright © 2019 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
22
Number Edges
60
Number Components
1
Network Density
0.12987012987013
Average Degree
2.72727272727273
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 in physiology and pathology v1.0.0 36%
Tau Antibody Targeting Pathological Species Blocks Neuronal Uptake and Interneuron Propagation of Tau in Vitro v1.0.0 36%
Tau Modifications v1.9.5 36%
Tau clearance mechanisms and their possible role in the pathogenesis of Alzheimer disease v1.0.0 32%
Tau Trimers Are the Minimal Propagation Unit Spontaneously Internalized to Seed Intracellular Aggregation v1.0.0 27%
Pseudophosphorylation of tau at S422 enhances SDS-stable dimer formation and impairs both anterograde and retrograde fast axonal transport. v1.0.0 27%
Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0 25%
Identification of the Tau phosphorylation pattern that drives its aggregation v1.0.0 23%
Caenorhabditis elegans models of tauopathy v1.0.0 23%
Molecular chaperones and regulation of tau quality control: strategies for drug discovery in tauopathies v1.0.0 23%

Sample Edges

Sample Nodes

bp(GO:aging)

In-Edges: 27 | Out-Edges: 61 | Explore Neighborhood | Download JSON

p(HGNC:MAPT)

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

a(HBP:"Tau aggregates")

In-Edges: 224 | Out-Edges: 71 | Children: 3 | Explore Neighborhood | Download JSON

p(MGI:Mapt)

In-Edges: 57 | Out-Edges: 59 | 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.