ReviewBulletin of mathematical biology2016
Mathematical Models for Immunology: Current State of the Art and Future Research Directions.
Review in Bulletin of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed.
- Multiscale modeling of T cell exhaustion: A mathematical framework integrating continuous dynamics with spatial heterogeneity.PLoS computational biology · 2026Article
- The SATvac model of CD8+ T cell expansion and contraction phases considering memory and effector cell differentiation.PLoS computational biology · 2026Article
- Multiscale modeling reveals synergy between CCL19 and PD-1 blockade in reshaping the TNBC microenvironment.NPJ systems biology and applications · 2026Article
- A Minimal Model Framework for Robust CAR-T Cell and Oncolytic Virus Combination Therapy.Research square · 2026Article
- Context-dependent immune regulation: a mechanistic and AI-enabled integrative framework.Frontiers in immunology · 2026Review
- Heterogeneous immune recovery after viral response through a dynamical model of feedback-driven persistence and clearance.Frontiers in immunology · 2026Article
- From empirical vaccinology to predictive systems-based vaccine design: multi-omics integration, artificial intelligence, and global equity challenges.Frontiers in systems biology · 2026Review
- Spatial topology and competitive access differentially shape early T cell priming in the lymph node: an agent-based modeling approach.Frontiers in immunology · 2026Article
- CAR T-cell and oncolytic virus dynamics and determinants of combination therapy success for glioblastoma.Mathematical biosciences · 2025Article
- Role of Tidal Volume on Ventilator-Induced Lung Injury Under Heterogeneous Immunological Capabilities: A Mathematical Model Study.Life (Basel, Switzerland) · 2025Article
- A Modular Mathematical Model of the Immune Response for Investigating the Pathogenesis of Infectious Diseases.Viruses · 2025Article
- Mathematical models and computational approaches in CAR-T therapeutics.Frontiers in immunology · 2025Review
- Artificial intelligence and machine learning in the development of vaccines and immunotherapeutics-yesterday, today, and tomorrow.Frontiers in artificial intelligence · 2025Review
- Multi-physiology modeling of the immune system in the era of precision immunotherapy.Frontiers in immunology · 2025Review
- Spatially fractionated GRID radiation potentiates immune-mediated tumor control.Radiation oncology (London, England) · 2024Article
- Using In silico models to predict lymphocyte activation and development in a data rich era.Immunoinformatics (Amsterdam, Netherlands) · 2024Article
- Inferring upstream regulatory genes of FOXP3 in human regulatory T cells from time-series transcriptomic data.NPJ systems biology and applications · 2024Article
- Pathomechanisms of Disturbances Underlying Chronic Disorders.Biomedicines · 2024Article
- Practical Considerations for Next-Generation Adjuvant Development and Translation.Pharmaceutics · 2023Review
- An agent-based model of monocyte differentiation into tumour-associated macrophages in chronic lymphocytic leukemia.iScience · 2023Article
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 advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years.
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.