ArticleBMC systems biology2014
NetworkViewer: visualizing biochemical reaction networks with embedded rendering of molecular interaction rules.
Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Rules railroad: Syntax-inspired diagrams for visualizing and understanding rule-based model specifications.PLoS computational biology · 2026Article
- Visualizing mechanistic models by integrating site-specific molecular details into reaction networks.Frontiers in molecular biosciences · 2025Article
- Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks.The journal of physical chemistry. A · 2024Article
- bnglViz: online visualization of rule-based models.Bioinformatics (Oxford, England) · 2024Article
- Omics and systems view of innate immune pathways.Proteomics · 2023Review
- Article
- Anosmin1 Shuttles Fgf to Facilitate Its Diffusion, Increase Its Local Concentration, and Induce Sensory Organs.Developmental cell · 2018Article
- Automated visualization of rule-based models.PLoS computational biology · 2017Article
- Modeling for (physical) biologists: an introduction to the rule-based approach.Physical biology · 2015Review
- MOSBIE: a tool for comparison and analysis of rule-based biochemical models.BMC bioinformatics · 2014Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundNetwork representations of cell-biological signaling processes frequently contain large numbers of interacting molecular and multi-molecular components that can exist in, and switch between, multiple biochemical and/or structural states. In addition, the interaction categories (associations, dissociations and transformations) in such networks cannot satisfactorily be mapped onto simple arrows connecting pairs of components since their specifications involve information such as reaction rates and conditions with regard to the states of the interacting components. This leads to the challenge of having to reconcile competing objectives: providing a high-level overview without omitting relevant information, and showing interaction specifics while not overwhelming users with too much detail displayed simultaneously. This problem is typically addressed by splitting the information required to understand a reaction network model into several categories that are rendered separately through combinations of visualizations and/or textual and tabular elements, requiring modelers to consult several sources to obtain comprehensive insights into the underlying assumptions of the model.
resultsWe report the development of an application, the Simmune NetworkViewer, that visualizes biochemical reaction networks using iconographic representations of protein interactions and the conditions under which the interactions take place using the same symbols that were used to specify the underlying model with the Simmune Modeler. This approach not only provides a coherent model representation but, moreover, following the principle of "overview first, zoom and filter, then details-on-demand," can generate an overview visualization of the global network and, upon user request, presents more detailed views of local sub-networks and the underlying reaction rules for selected interactions. This visual integration of information would be difficult to achieve with static network representations or approaches that use scripted model specifications without offering simple but detailed symbolic representations of molecular interactions, their conditions and consequences in terms of biochemical modifications.
conclusionsThe Simmune NetworkViewer provides concise, yet comprehensive visualizations of reaction networks created in the Simmune framework. In the near future, by adopting the upcoming SBML standard for encoding multi-component, multi-state molecular complexes and their interactions as input, the NetworkViewer will, moreover, be able to offer such visualization for any rule-based model that can be exported to that standard.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.