ReviewTrends in immunology2017
Solving Immunology?
Review in Trends in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed, 52 citations in OpenAlex.
- Combinatorial (bio-geo-temporal) and non-combinatorial analysis of the COVID-19 dissemination that affected Georgia (the country) in 2021.Frontiers in public health · 2026Article
- Systems Human Immunology and AI: Immune Setpoint and Immune Health.Annual review of immunology · 2025Review
- Multiscale information processing in the immune system.Frontiers in immunology · 2025Review
- Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system.Nature immunology · 2024Review
- Sex and gender in infection and immunity: addressing the bottlenecks from basic science to public health and clinical applications.Royal Society open science · 2023Article
- Towards systems immunology of critical illness at scale: from single cell 'omics to digital twins.Trends in immunology · 2023Review
- Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Systems biology of malaria explored with nonhuman primates.Malaria journal · 2022Review
- A roadmap for translational cancer glycoimmunology at single cell resolution.Journal of experimental & clinical cancer research : CR · 2022Review
- Mapping CAR T-Cell Design Space Using Agent-Based Models.Frontiers in molecular biosciences · 2022Article
- Molecular design of the γδT cell receptor ectodomain encodes biologically fit ligand recognition in the absence of mechanosensing.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Integrative genomics of the mammalian alveolar macrophage response to intracellular mycobacteria.BMC genomics · 2021Article
- Cancer immune control dynamics: a clinical data driven model of systemic immunity in patients with metastatic melanoma.BMC bioinformatics · 2021Article
- Aging-induced fragility of the immune system.Journal of theoretical biology · 2021Article
- A case for the reuse and adaptation of mechanistic computational models to study transplant immunology.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020Review
- Experimental Control of Macrophage Pro-Inflammatory Dynamics Using Predictive Models.Frontiers in bioengineering and biotechnology · 2020Article
- Dynamical modeling of pro- and anti-inflammatory cytokines in the early stage of septic shock.In silico biology · 2020Article
- High-resolution computational modeling of immune responses in the gut.GigaScience · 2019Article
- Advanced model systems and tools for basic and translational human immunology.Genome medicine · 2018Review
- Applications of mechanistic modelling to clinical and experimental immunology: an emerging technology to accelerate immunotherapeutic discovery and development.Clinical and experimental immunology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 13 institutions in 2 countries.
Funding
Abstract
Emergent responses of the immune system result from the integration of molecular and cellular networks over time and across multiple organs. High-content and high-throughput analysis technologies, concomitantly with data-driven and mechanistic modeling, hold promise for the systematic interrogation of these complex pathways. However, connecting genetic variation and molecular mechanisms to individual phenotypes and health outcomes has proven elusive. Gaps remain in data, and disagreements persist about the value of mechanistic modeling for immunology. Here, we present the perspectives that emerged from the National Institute of Allergy and Infectious Disease (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regarding the potential synergy of high-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disease and to accelerate the translation of these insights into therapies.
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.