ReviewFrontiers in immunology2014
An Interaction Library for the FcεRI Signaling Network.
Review in Frontiers in immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 22 citations in OpenAlex.
- Lipid metabolism-related molecular typing and prognostic characteristics of cutaneous melanoma.Translational cancer research · 2026Article
- 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
- Limits on the accuracy of contact inhibition of locomotion.Physical review. E · 2024Article
- My path in the company of chemistry.Pure and applied chemistry. Chimie pure et appliquee · 2022Article
- Kinomics platform using GBM tissue identifies BTK as being associated with higher patient survival.Life science alliance · 2021Article
- Parallel Tempering with Lasso for model reduction in systems biology.PLoS computational biology · 2020Article
- Efficient anticorrelated variance reduction for stochastic simulation of biochemical reactions.IET systems biology · 2019Article
- Automated visualization of rule-based models.PLoS computational biology · 2017Article
- Simple biochemical networks allow accurate sensing of multiple ligands with a single receptor.PLoS computational biology · 2017Article
- Modeling for (physical) biologists: an introduction to the rule-based approach.Physical biology · 2015Review
- Immune system modeling and analysis.Frontiers in immunology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein-protein and protein-lipid interactions. This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP3 at the plasma membrane and the soluble second messenger IP3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.
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.