Provenance

Upload
charles.hoyt@scai.fraunhofer.de at 2019-02-27 16:20:55.983217
Authors
Lingling Xu
Contact
charles.hoyt@scai.fraunhofer.de
License
CC BY 4.0
Copyright
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
94
Number Edges
173
Number Components
2
Network Density
0.0197895218485472
Average Degree
1.84042553191489
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
albuquerque2009 v1.0.0 26%
Nicotinic receptors: allosteric transitions and therapeutic targets in the nervous system v1.0.0 22%
Nicotinic α4β2 acetylcholine receptors and cognitive function in Parkinson's disease v1.0.0 22%
NACHO Mediates Nicotinic Acetylcholine Receptor Function throughout the Brain v1.0.0 19%
Selective activation of α7 nicotinic acetylcholine receptor by PHA-543613 improves Aβ25-35-mediated cognitive deficits in mice v1.0.0 18%
Neuronal Nicotinic Acetylcholine Receptor Structure and Function and Response to Nicotine v1.0.1 18%
Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0 17%
The Nicotinic Acetylcholine Receptor: The Founding Father of the Pentameric Ligand-gated Ion Channel Superfamily v1.0.1 17%
Alzheimer's Disease: Targeting the Cholinergic System v1.0.0 16%
Neural Systems Governed by Nicotinic Acetylcholine Receptors: Emerging Hypotheses v1.0.0 16%

Sample Edges

Sample Nodes

path(MESH:"Alzheimer Disease")

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

path(MESH:Memory)

In-Edges: 6 | Out-Edges: 3 | 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.