ArticlePLoS computational biology2025
SBMLNetwork: A framework for standards-based visualization of biochemical models.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Antimony 3: Extending human-readable model definitions for SBML Level 3 Core and Packages.PLoS computational biology · 2026Article
- Systems biology during 20 years of PLoS Computational Biology.PLoS computational biology · 2026Article
- Antimony 3: Extending human-readable model definitions for SBML Level 3 Core and Packages.bioRxiv : the preprint server for biology · 2026Article
- A standardized workflow for kinetic metabolic model curation and dissemination.PLoS computational biology · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
SBMLNetwork is an open-source software library that makes the SBML Layout and Render packages practical for standards-based visualization of biochemical models. Current tools often manage model visualization data in custom-designed, tool-specific formats and store it separately from the model itself, hindering interoperability, reproducibility, and the seamless integration of visualization with model data. SBMLNetwork addresses these limitations by building directly on the SBML Layout and Render specifications, automating the generation of standards-compliant visualization data, offering a modular implementation with broad integration support, and providing a robust API tailored to the needs of systems biology researchers. We illustrate the capabilities of SBMLNetwork across key visualization tasks, including SBGN-compliant visualization, application of predefined style templates, layout arrangement to reflect pathway logic, and integration of model data into network diagrams. These examples demonstrate how SBMLNetwork enables high-level visualization features and seamlessly translate user intent into reproducible outputs that support both structural representation and dynamic data visualization within the SBML model. SBMLNetwork is freely available at https://github.com/sys-bio/SBMLNetwork under the MIT license.
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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.