ArticleMolecular bioSystems2011
Guidelines for visualizing and annotating rule-based models.
Article in Molecular bioSystems, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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.
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
24 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
- Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes.Molecular biology of the cell · 2020Article
- Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling.Cell systems · 2018Article
- The Kappa platform for rule-based modeling.Bioinformatics (Oxford, England) · 2018Article
- Automated visualization of rule-based models.PLoS computational biology · 2017Article
- Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.Bioinformatics (Oxford, England) · 2016Article
- Modeling for (physical) biologists: an introduction to the rule-based approach.Physical biology · 2015Review
- Computational analysis of an autophagy/translation switch based on mutual inhibition of MTORC1 and ULK1.PloS one · 2015Article
- NetworkViewer: visualizing biochemical reaction networks with embedded rendering of molecular interaction rules.BMC systems biology · 2014Article
- An Interaction Library for the FcεRI Signaling Network.Frontiers in immunology · 2014Review
- Article
- Disease-enhancing antibodies improve the efficacy of bacterial toxin-neutralizing antibodies.Cell host & microbe · 2013Article
- A predictive mathematical model of the DNA damage G2 checkpoint.Journal of theoretical biology · 2013Article
- Modeling the effect of APC truncation on destruction complex function in colorectal cancer cells.PLoS computational biology · 2013Article
- Programming biological models in Python using PySB.Molecular systems biology · 2013Article
- The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail.BMC bioinformatics · 2012Article
- Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling.BMC systems biology · 2012Article
- A computational model for early events in B cell antigen receptor signaling: analysis of the roles of Lyn and Fyn.Journal of immunology (Baltimore, Md. : 1950) · 2012Article
- A framework for mapping, visualisation and automatic model creation of signal-transduction networks.Molecular systems biology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.
Indexed as
Identifiers
What OpenQuestion holds
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.