CBN database

What is CBN?

The Causal Biological Networks (CBN) database is composed of multiple versions of over 120 modular, manually curated, BEL-scripted biological network models supported by over 80,000 unique pieces of evidence from the scientific literature.

They represent causal signaling pathways across a wide range of biological processes including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and vascular systems.

How can I cite CBN?

If you have used CBN as part of your research, please cite:

Causal Biological Network (CBN) Database: Causal Biological Network (CBN) Database: A Comprehensive Platform of Causal Biological Network Models Focused on the Pulmonary and Vascular Systems. Database. bav030. 2015

Which networks are present in CBN?

We have uploaded in CBN our collection of biological network models reflecting causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in pulmonary and vascular systems.

Causal Biological Networks

What are nodes and edges in the networks?

  1. Node (e.g. p(HGNC:EGFR), bp(GO:"Oxidative Process"), a(CHEBI:Water)
  2. Network Edge - comprised of 1, 2 and 3 (node -> edge -> node)

Network Edge Examples:

  • p(HGNC:IL6) -> r(HGNC:ENO1)
  • p(HGNC:IL6) -> r(HGNC:XBP1)

What are Supporting Statements?

Zoom Network Edge: (1) -> (2)

  1. Network Edge statement – each edge exists because there is at least one Evidence Statement that supports it, consisting of a node connected to another node by a relationship
  2. Evidence statement - Each edge statement is supported by one or more Evidence (BEL) statements that provide the evidence for the edge, including the citation (usually PubMed ID) and experimental context

How are Causal and Non-causal Edges defined?

Causal statements connect subject and object terms with a causal increase (symbol: -> ) or decrease (symbol: -| )relationship. Subject terms can be an abundance or process (including activities and transformations) and object terms can be either an abundance, a process, or a second BEL Statement.

A non-causal statement is any statement that does not have an increase or decrease relationship (e.g. positiveCorrelation or association).

How were the networks constructed?

Network construction is a multi-step process:

  1. Careful selection of model boundaries, i.e., selection of appropriate tissue/cell context and biological processes to be included in the model.
  2. Review of scientific literature to extract relevant causal relationships, resulting in the construction of the literature model scaffold composed of nodes and edges, representing causal relationships between the nodes extracted from the Selventa Knowledgebase.
  3. In the network verification and extension step, reverse causal reasoning (RCR) was used to mine molecular profiling data in the context of the Selventa Knowledgebase. RCR is a reverse engineering algorithm to identify biological mechanisms that are statistically significant explanations for differential measurements in a molecular profiling data set. RCR analysis of relevant (i.e., within defined boundaries) data sets facilitated the identification and inclusion, where appropriate, of additional biological processes derived from these experimental data that may not be apparent from evaluation of scientific literature dedicated to the biological process of interest. Attentive expert curation during the integration of each newly identified mechanistic node into evolving networks that are iteratively derived from data sets ensured the continuity of relevant boundary conditions during network construction.

The final networks reflect the value of combined use of molecular profiling data with carefully considered use of prior biological knowledge of cause-and-effect relationships.

To learn more about network construction, watch our videos and webinars at the following links:

What are network boundaries?

The networks are built within defined biological and context boundaries: signalling pathways and molecules important to define biological processes of interest are scoped out based on experts' knowledge and review articles. Moreover, context boundaries (species, tissues, cell types, experiment types) are set for the provenance of the evidences and datasets used for network building. This is unlike other common approaches for building pathway or connectivity maps where connections are often represented without regard for tissue or disease contexts.

Specific network boundaries for each network are specified in respective publications.

Are the networks already published?

Yes, the version 1.0 of all networks have been published already in 6 collections:

Why are there different versions of networks?

Version 1.0 of the network is the original networks as they were published. Further enhancements added COPD-relevant biology to the networks. Moreover, some of the networks were verified in the sbv IMPROVER network verification challenge and their updated versions are also included.

The figure below summarizes the network construction process as well as the iterative refinement producing new network versions.

  • Version 1.0 - Networks as they were originally published
  • Version 1.1 - Networks in openBEL
  • Version 1.2 - Networks after first network verification challenge (NVC1)
  • Version 1.3 - Consolidated networks prior to second network verification challenge (NVC2)
  • Version 2.0 - Networks after NVC2

Where can I learn more about the networks in CBN?

You may look at the respective publications. Moreover, there is a short video explaining the networks:

And a series of webinars that were developed for the sbv IMPROVER network verification challenge that was built to verify some of the networks. https://sbvimprover.com/network-verification/videos-seminars/webinars


What is BEL?

BEL stands for Biological Expression Language. BEL was designed to capture biological cause-and-effect relationships with associated experimental context from disparate sources, and to facilitate the encoding of directional relationships within computable biological network models. It is both human readable and computable.

Where can I find more resources on BEL?

Why is a gene present multiple times in a network?

Owing to BELs' representational flexibility, the networks can capture a wide range of biological molecules including proteins, complexes, DNA variants, coding and non-coding RNA, chemicals, lipids, methylation states or other modifications (e.g., phosphorylation). For example, BEL allows for the discrimination between the abundance of a protein and its activity, so the same gene name may appear multiple times, depending on the biological molecule it represents.

Can I translate the BEL network into another language?

The openBEL community is working on developing ways to translate BEL into RTF and SBML.

Network download

How can I download a network?

To download a network, simply locate the desired network using the "Search for Network" functionality on the home page. Click the "Export" link and select an export format. The network will be downloaded through your browser and can be saved to your computer.

In which format can I download networks?

You can download the networks as:

  • SIF (simple interchanged file) file, which is basically a list of node-edge-node, which allows to see all edges and to reconstruct the network in software such as cytoscape.
  • JGF (JSON Graph File) file, which captures the basic graph structure in a convenient to use format and allows for the use of metadata objects in the graph, nodes and edges. This metadata can be used for any other graph data that needs to be managed in your graph data files (e.g. graph layout, styling, algorithm results, etc). Details on the JGF files can be found here www.json-graph-format.info

Can I download and use the networks for my own research?

You can download and use the networks for your own research. If you do, please cite:

Causal Biological Network (CBN) Database: Causal Biological Network (CBN) Database: A Comprehensive Platform of Causal Biological Network Models Focused on the Pulmonary and Vascular Systems. Database. bav030. 2015

CBN website

How often are networks uploaded?

CBN will regularly be updated. New versions of existing networks or new networks may be uploaded.

Can I contribute my own network and upload it in CBN?

We will consider adding curated networks from the scientific community to CBN. At present, only BEL networks can be uploaded. When SMBL/BioPAX <-> bel converters will be developed, we will also consider additional network types. if you have a specific question, please contact us at CausalBiologicalNetworks.RD@pmi.com

CBN and Bionet

Some of the networks are available on the bionet.sbvimprover.com platform awaiting crowd-verification. To learn more about this challenge, and join, go to the website.

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