ArticleJournal of the Royal Society, Interface2009
Constraint-based network model of pathogen-immune system interactions.
Article in Journal of the Royal Society, Interface, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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.
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Who cites it
19 citing papers in PubMed, 53 citations in OpenAlex.
- Gastrointestinal helminths increaseeLife · 2022Article
- Boolean modelling in plant biology.Quantitative plant biology · 2022Review
- Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy.PLoS computational biology · 2020Article
- Simulation of the Dynamics of Primary Immunodeficiencies in B Cells.Frontiers in immunology · 2018Article
- Discrete Dynamical Modeling of Influenza Virus Infection Suggests Age-Dependent Differences in Immunity.Journal of virology · 2017Article
- Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.Briefings in functional genomics · 2017Review
- Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.Frontiers in physiology · 2017Review
- Article
- Boolean Modeling of Cellular and Molecular Pathways Involved in Influenza Infection.Computational and mathematical methods in medicine · 2016Article
- Flagellar motility of the pathogenic spirochetes.Seminars in cell & developmental biology · 2015Review
- Iron acquisition and oxidative stress response in aspergillus fumigatus.BMC systems biology · 2015Article
- Seven challenges in modeling vaccine preventable diseases.Epidemics · 2015Article
- Spatiotemporal evolution of erythema migrans, the hallmark rash of Lyme disease.Biophysical journal · 2014Article
- Article
- Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks.Cell communication and signaling : CCS · 2013Article
- Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth.PLoS computational biology · 2012Article
- Snapshot of spatio-temporal cytokine responses to single and co-infections with helminths and bacteria.Results in immunology · 2011Article
- Immune regulation of a chronic bacteria infection and consequences for pathogen transmission.BMC microbiology · 2010Article
- Dynamic models of immune responses: what is the ideal level of detail?Theoretical biology & medical modelling · 2010Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Pathogenic bacteria such as Bordetella bronchiseptica modulate host immune responses to enable their establishment and persistence; however, the immune response is generally successful in clearing these bacteria. Here, we model the dynamic outcome of the interplay between host immune components and B. bronchiseptica virulence factors. The model extends our previously published interaction network of B. bronchiseptica and includes the existing experimental information on the relative timing of IL10 and IFNgamma activation in the form of qualitative inequalities. The current model improves the previous one in two directions: (i) by augmenting the network with new nodes with specific function in T helper cell differentiation and effector mechanisms and (ii) by using a dynamic approach that allows us to quantify node states and mechanisms revealed to be important from our previous model. The model makes predictions about the time scales of each process, the activity thresholds of each node and novel regulatory interactions. For example, the model predicts that the activity threshold of IL4 is higher than that of IL12 and that pro-inflammatory cytokines regulate the activity of Th2 cells. Some of these predictions are supported by the literature, and many can serve as targets of future experiments.
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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.