ArticleScientific reports2017
Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis.JID innovations : skin science from molecules to population health · 2026Review
- Petri net modeling and simulation of post-transcriptional regulatory networks of human embryonic stem cell (hESC) differentiation to cardiomyocytes.Journal of integrative bioinformatics · 2025Article
- Review
- Exploring attractor bifurcations in Boolean networks.BMC bioinformatics · 2022Article
- Transcriptional programming of immunoregulatory responses in human Langerhans cells.Frontiers in immunology · 2022Article
- An IRF1-IRF4 Toggle-Switch Controls Tolerogenic and Immunogenic Transcriptional Programming in Human Langerhans Cells.Frontiers in immunology · 2021Article
- Petri Net modelling approach for analysing the behaviour ofIET systems biology · 2020Article
- A Role of Inflammation and Immunity in Essential Hypertension-Modeled and Analyzed Using Petri Nets.International journal of molecular sciences · 2020Article
- Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches.IET systems biology · 2020Article
- Genomic programming of IRF4-expressing human Langerhans cells.Nature communications · 2020Article
- Human and computational models of atopic dermatitis: A review and perspectives by an expert panel of the International Eczema Council.The Journal of allergy and clinical immunology · 2019Review
- Increasing Upstream Chromatin Long-Range Interactions May Favor Induction of Circular RNAs in LysoPC-Activated Human Aortic Endothelial Cells.Frontiers in physiology · 2019Article
- Model of the adaptive immune response system against HCV infection reveals potential immunomodulatory agents for combination therapy.Scientific reports · 2018Article
- A graphical and computational modeling platform for biological pathways.Nature protocols · 2018Article
- MicroRNA pharmacogenomics based integrated model of miR-17-92 cluster in sorafenib resistant HCC cells reveals a strategy to forestall drug resistance.Scientific reports · 2017Article
- Langerhans Cells-Programmed by the Epidermis.Frontiers in immunology · 2017Review
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Authors and funding
5 authors.
Funding
Abstract
Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-γ production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.
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