Biological Network Models

Biological Network Models

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In the sbv IMPROVER Network Verification Challenge (NVC), 50 network models1-5 are presented for verification by participants. The networks is split into 5 tracks: cell stress, cell fate, cell proliferation, immune and tissue response. The evidence is primarily based on human, non-diseased respiratory tissue biology augmented with chronic obstructive respiratory disease biology.


Network models included in the challenge

This section provides an overview of the structure of the network models and their biology.


Structure of the network models in the Network Verification Challenge

  • Nodes: A wide range of biological entities are represented as nodes in the network models. They include proteins, DNA variants, non-coding RNA, phenotypic or clinical observations, chemicals, lipids, methylation states, and other modifications (e.g., phosphorylation). Existing nodes were identified using biological databases such as SwissProt (, EntrezGene (, Rat Genome Database (, and ChEBI (
  • Edges: The causal or correlative nature of relationships between nodes is represented as an edge. This allows the biological intent of the network model to be easily digested by a scientist. Examples of relationships include:
      • TGF Beta 1 increases SMAD1
      • MDM2 negatively regulates the activity of p53
  • Context: Each edge is constructed within precisely defined contextual boundaries, based on a literature reference to justify the edge’s existence. The context of an edge may include species, tissue, cell and disease.
  • Written in BEL: The nodes and edges in the network model are captured in BEL, a computable language designed for network biology. For more information, please see: Biological Network Representation with BEL
  • Interactive and dynamic: The networks, as implemented on the NVC website, are dynamic. They can be modified as new knowledge becomes available and current edges and pieces of evidences are verified by the community.


Biology modeled in the Network Verification Challenge networks

The network models selected for the NVC were derived from CausalBioNet network models and represent important biological processes implicated in human lung physiology and specific processes related to COPD.

  • Non-disease networks:
      • Cell proliferation, cellular stress, cell fate, pulmonary inflammation, tissue repair and angiogenesis.
  • Chronic obstructive pulmonary disease (COPD) networks
      • B-cell Activation and T-cell Recruitment and Activation sub-networks to represent immune processes and their role in COPD, and
      • Extracellular matrix (ECM) Degradation and Efferocytosis sub-networks were constructed by heavily modifying healthy models to specifically represent COPD-relevant mechanisms.
  • Species Context: Primarily human, although mouse and rat evidence was included when supporting literature from human context was not available.
  • Tissue context: Primarily non-diseased respiratory tissue biology.
  • Disease context: Healthy tissue augmented with chronic obstructive pulmonary disease biology only (e.g. lung cancer context was excluded).

Proof-of-principle verification of these network models has been published previously. One recent study demonstrated how CausalBioNet Network models can be used to identify and quantitate chemically induced biological changes6, a feature that might be especially useful to the toxicology community7.

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