ReviewNature reviews. Immunology2020
Simulation modelling for immunologists.
Review in Nature reviews. Immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mechanistic models of Rift Valley fever virus transmission: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- Different factors control long-term versus short-term outcomes for bacterial colonisation of a urinary catheter.Nature communications · 2025Article
- Systems Human Immunology and AI: Immune Setpoint and Immune Health.Annual review of immunology · 2025Review
- Immune targeting and host-protective effects of the latent stage of Toxoplasma gondii.Nature microbiology · 2025Article
- The dawn of biophysical representations in computational immunology.QRB discovery · 2025Review
- Systems immunology: When systems biology meets immunology.Frontiers in immunology · 2025Review
- Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.Epidemics · 2024Review
- Immune digital twins for complex human pathologies: applications, limitations, and challenges.NPJ systems biology and applications · 2024Review
- Quantitative principles of microbial metabolism shared across scales.Nature microbiology · 2024Review
- Decoding immune kinetics: unveiling secrets using custom-built mathematical models.Nature methods · 2024Article
- Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system.Nature immunology · 2024Review
- A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis.Frontiers in applied mathematics and statistics · 2024Article
- Estimating the contribution of CD4 T cell subset proliferation and differentiation to HIV persistence.Nature communications · 2023Article
- Tensor-based insights into systems immunity and infectious disease.Trends in immunology · 2023Article
- Metabolomics meets systems immunology.EMBO reports · 2023Review
- Embracing complexity in sepsis.Critical care (London, England) · 2023Review
- Article
- Modulating Immune Response in Viral Infection for Quantitative Forecasts of Drug Efficacy.Pharmaceutics · 2023Review
- cDC1 coordinate innate and adaptive responses in the omentum required for T cell priming and memory.Science immunology · 2022Article
- Mathematical Modeling of Proliferative Immune Response Initiated by Interactions Between Classical Antigen-Presenting Cells Under Joint Antagonistic IL-2 and IL-4 Signaling.Frontiers in molecular biosciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The immune system is inordinately complex with many interacting components determining overall outcomes. Mathematical and computational modelling provides a useful way in which the various contributions of different immunological components can be probed in an integrated manner. Here, we provide an introductory overview and review of mechanistic simulation models. We start out by briefly defining these types of models and contrasting them to other model types that are relevant to the field of immunology. We follow with a few specific examples and then review the different ways one can use such models to answer immunological questions. While our examples focus on immune responses to infection, the overall ideas and descriptions of model uses can be applied to any area of immunology.
Indexed as
Identifiers
31804613What 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.