From the home page, click List Networks, find your network, and select "Summarize".
This web application organizes high level statistical information about a network, such as the number of nodes, edges, author contributions, citation contributions, and provenance information as well as global network statistics such as the average node degree, network density, number of weakly connected components, etc. When appropriate, it proves feedback on syntax and semantics of the source BEL document to assist in curation.
Finally, the summary page provides an assessment of the "Biological Grammar", or the biological validity of statements. These analysis include identification of contradictory edges, unstable biological motifs in pairs and triplets of nodes, and other information that is inferred to be missing or incomplete.
A query contain three steps:
Finally, the results of queries can be summarized, downloaded in many formats, or explored.
The results of query can be explored interactively with the Biological Network Explorer. Its tools panel contains an extended query builder interface that can be used to apply additional transformations. Network algorithms can be readily applied to networks such as path searches, centrality calculations, and overlaying of external data. These data can come from differential expression experiments, or directly from the results of the Heat Diffusion workflow, which is explained below.
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.