Provenance

Upload
charles.hoyt@scai.fraunhofer.de at 2019-03-15 15:44:03.509962
Authors
Sandra Spalek
Contact
charles.hoyt@scai.fraunhofer.de
License
CC BY 4.0
Copyright
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
123
Number Edges
226
Number Components
2
Network Density
0.0150606424097028
Average Degree
1.83739837398374
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
Alzheimer’s disease and the autophagic-lysosomal system v1.0.0 31%
The Ubiquitin–Proteasome System and the Autophagic–Lysosomal System in Alzheimer Disease v1.0.0 30%
Identification of a novel aspartic protease (Asp 2) as beta-secretase v1.0.0 30%
The Ubiquitin Proteasome System in Neurodegenerative Diseases: Sometimes the Chicken, Sometimes the Egg v1.0.0 24%
Protein aggregation can inhibit clathrin-mediated endocytosis by chaperone competition v1.0.0 23%
Pathological missorting of endogenous MAPT/Tau in neurons caused by failure of protein degradation systems v1.0.1 22%
Perilous journey: a tour of the ubiquitin–proteasome system v1.0.0 21%
Promoting the clearance of neurotoxic proteins in neurodegenerative disorders of ageing v1.0.0 20%
Carboxy terminus heat shock protein 70 interacting protein reduces tau-associated degenerative changes v1.0.0 19%
Interplay of pathogenic forms of human tau with different autophagic pathways v1.0.1 18%

Sample Edges

a(CHEBI:"alpha,alpha-trehalose") increases bp(GO:autophagy) View Subject | View Object

In addition, inducing autophagy in an TOR-independent manner using lithium [53] or trehalose [54–56] has been shown to accelerate clearance of disease proteins in vitro [56] and protect against neurodegeneration in mouse and Drosophila models of Huntington’s disease [53,54]. PubMed:18930136

Annotations
MeSH
Huntington Disease

Sample Nodes

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.