SC-CC (Biological Networks)
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This network dataset is in the category of Biological Networks
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Metadata
| Category | Sparse Networks |
| Collection | Biological Networks |
| Tags | |
| Source | WormNet; see http://www.inetbio.org/wormnet/ |
| Short | Gene functional associations |
| Vertex type | Genes |
| Edge type | Lines |
| Format | Undirected |
| Edge weights | Weighted |
| Description | WormNet: a network by integration of all data-type-specific networks (CE-CX, CE-GN, CE-GT, CE-HT, CE-LC, CE-PG, DM-CX, DM-HT, DM-LC, DR-CX, HS-CX, HS-HT, HS-LC, SC-CC, SC-CX, SC-HT, SC-LC, SC-TS) by modified Bayesian integration. |
Please cite the following if you use the data:
Note that if you transform/preprocess the data, please consider sharing the data by uploading it along with the details on the transformation and reference to any published materials using it.
@inproceedings{nr,
title={The Network Data Repository with Interactive Graph Analytics and Visualization},
author={Ryan A. Rossi and Nesreen K. Ahmed},
booktitle={AAAI},
url={http://networkrepository.com},
year={2015}
}
@article{cho2014wormnet,
title={WormNet v3: a network-assisted hypothesis-generating server for Caenorhabditis elegans},
author={Cho, Ara and Shin, Junha and Hwang, Sohyun and Kim, Chanyoung and Shim, Hongseok and Kim, Hyojin and Kim, Hanhae and Lee, Insuk},
journal={Nucleic acids research},
volume={42},
number={W1},
pages={W76--W82},
year={2014},
publisher={Oxford University Press}
}
Network Data Statistics
| Nodes | 2.2K |
| Edges | 34.9K |
| Density | 0.0141225 |
| Maximum degree | 571 |
| Minimum degree | 1 |
| Average degree | 31 |
| Assortativity | -0.152083 |
| Number of triangles | 595.7K |
| Average number of triangles | 267 |
| Maximum number of triangles | 6.7K |
| Average clustering coefficient | 0.413279 |
| Fraction of closed triangles | 0.194507 |
| Maximum k-core | 69 |
| Lower bound of Maximum Clique | 10 |
Network Data Preview
Interactive visualization of bio-SC-CC's graph structure
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Interactive Visualization of Node-level Properties and Statistics
Tools for Interactive Exploration of Node-level Statistics
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- Each point represents a node (vertex) in the graph.
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Interactive Visualization of Node-level Feature Distributions
Node-level Feature Distributions
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