Evidence map›Paper›PMID 38814806›Full record

ArticleBioinformatics (Oxford, England)2024

bnglViz: online visualization of rule-based models.

Noah Liguori-Bills, Michael L Blinov

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Noah Liguori-BillsMarine Earth and Atmospheric Sciences Department, North Carolina State University, Raleigh, NC 27695, United States.
Michael L BlinovR. D. Berlin Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, Farmington, CT 06030, United States.ORCID 0000-0002-9363-9705

Funding

TR&D3: Standards and Tools for Simulator Composition and Credibility portalP41EB023912 · NIBIB · UNIVERSITY OF WASHINGTON · PI Ion I. Moraru, HERBERT M. SAURO · 2018 to 2026
$11.4M
Mechanistic Modeling of Cellular SystemsR24GM137787 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI Pedro Mendes, Ion I. Moraru · 2020 to 2026
$8.9M
NIBIB NIH HHS P41 EB023912NIH HHS R24 GM137787
6 · The paper itself

Abstract

motivationRule-based modeling is a powerful method to describe and simulate interactions among multi-site molecules and multi-molecular species, accounting for the internal connectivity of molecules in chemical species. This modeling technique is implemented in BioNetGen software that is used by various tools and software frameworks, such as BioNetGen stand-alone software, NFSim simulation engine, Virtual Cell simulation and modeling framework, SmolDyn and PySB software tools. These tools exchange models using BioNetGen scripting language (BNGL). Until now, there was no online visualization of such rule-based models. Modelers and researchers reading the manuscripts describing rule-based models had to learn BNGL scripting or master one of these tools to understand the models.

resultsHere, we introduce bnglViz, an online platform for visualizing BNGL files as graphical cartoons, empowering researchers to grasp the nuances of rule-based models swiftly and efficiently, and making the exploration of complex biological systems more accessible than ever before. The produced visualizations can be used as supplemental figures in publications or as a way to annotate BNGL models on web repositories. AVAILABILITY AND IMPLEMENTATION: Available at https://bnglviz.github.io/.

Indexed as

SoftwareComputational BiologyComputer SimulationInternetModels, Biological

Identifiers

PMID38814806
PMCPMC11176710

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.