ArticleBMC bioinformatics2019
Deriving a Boolean dynamics to reveal macrophage activation with in vitro temporal cytokine expression profiles.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Inhibition of TLR4 mitigates sensorineural hearing loss resulting from cochlear inflammation.Molecular medicine (Cambridge, Mass.) · 2025Article
- Uncoding the interdependency of tumor microenvironment and macrophage polarization: insights from a continuous network approach.Frontiers in immunology · 2023Article
- CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19.Pathogens (Basel, Switzerland) · 2022Article
- Computational Modeling of Macrophage Iron Sequestration during Host Defense against Aspergillus.mSphere · 2022Article
- Systems biology of angiogenesis signaling: Computational models and omics.WIREs mechanisms of disease · 2022Review
- Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells.Computational and structural biotechnology journal · 2022Review
- Cyclic Attractors Are Critical for Macrophage Differentiation, Heterogeneity, and Plasticity.Frontiers in molecular biosciences · 2022Article
- Boolean modeling reveals that cyclic attractors in macrophage polarization serve as reservoirs of states to balance external perturbations from the tumor microenvironment.Frontiers in immunology · 2022Article
- A data-driven computational model enables integrative and mechanistic characterization of dynamic macrophage polarization.iScience · 2021Article
- Insights on TAM Formation from a Boolean Model of Macrophage Polarization Based on In Vitro Studies.Cancers · 2020Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundMacrophages show versatile functions in innate immunity, infectious diseases, and progression of cancers and cardiovascular diseases. These versatile functions of macrophages are conducted by different macrophage phenotypes classified as classically activated macrophages and alternatively activated macrophages due to different stimuli in the complex in vivo cytokine environment. Dissecting the regulation of macrophage activations will have a significant impact on disease progression and therapeutic strategy. Mathematical modeling of macrophage activation can improve the understanding of this biological process through quantitative analysis and provide guidance to facilitate future experimental design. However, few results have been reported for a complete model of macrophage activation patterns.
resultsWe globally searched and reviewed literature for macrophage activation from PubMed databases and screened the published experimental results. Temporal in vitro macrophage cytokine expression profiles from published results were selected to establish Boolean network models for macrophage activation patterns in response to three different stimuli. A combination of modeling methods including clustering, binarization, linear programming (LP), Boolean function determination, and semi-tensor product was applied to establish Boolean networks to quantify three macrophage activation patterns. The structure of the networks was confirmed based on protein-protein-interaction databases, pathway databases, and published experimental results. Computational predictions of the network evolution were compared against real experimental results to validate the effectiveness of the Boolean network models.
conclusionThree macrophage activation core evolution maps were established based on the Boolean networks using Matlab. Cytokine signatures of macrophage activation patterns were identified, providing a possible determination of macrophage activations using extracellular cytokine measurements.
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