Provenance

Upload
charles.hoyt@scai.fraunhofer.de at 2019-02-27 16:16:44.995331
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
124
Number Edges
246
Number Components
2
Network Density
0.0161290322580645
Average Degree
1.98387096774194
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
Selective activation of α7 nicotinic acetylcholine receptor by PHA-543613 improves Aβ25-35-mediated cognitive deficits in mice v1.0.0 55%
A role for b2* nicotinic receptors in a model of local amyloid pathology induced in dentate gyrus v1.0.0 43%
Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0 38%
NACHO Mediates Nicotinic Acetylcholine Receptor Function throughout the Brain v1.0.0 35%
Nicotinic Receptor Abnormalities of Alzheimer’s Disease: Therapeutic Implications v1.0.0 34%
Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0 33%
Nicotinic acetylcholine receptor signalling: roles in Alzheimer's disease and amyloid neuroprotection. v1.0.0 32%
The alpha7 nicotinic receptor agonist 4OH-GTS-21 protects axotomized septohippocampal cholinergic neurons in wild type but not amyloid-overexpressing transgenic mice v1.0.0 31%
Alzheimer's disease pathological lesions activate the spleen tyrosine kinase. v1.0.0 29%
Neuronal Nicotinic Acetylcholine Receptor Structure and Function and Response to Nicotine v1.0.1 29%

Sample Edges

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.