ArticlePLoS computational biology2012
Which of our modeling predictions are robust?
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Control theory helps to resolve the measles paradox.Royal Society open science · 2021Article
- Stochastic dynamics of Francisella tularensis infection and replication.PLoS computational biology · 2020Article
- Dynamics of virus and immune response in multi-epitope network.Journal of mathematical biology · 2018Article
- RNA Virus Evolution via a Quasispecies-Based Model Reveals a Drug Target with a High Barrier to Resistance.Viruses · 2017Article
- How to deal with parameters for whole-cell modelling.Journal of the Royal Society, Interface · 2017Review
- Prediction of the containment of HIV infection by antiretroviral therapy - a variable structure control approach.IET systems biology · 2017Article
- Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics.PLoS biology · 2016Article
- Notwithstanding Circumstantial Alibis, Cytotoxic T Cells Can Be Major Killers of HIV-1-Infected Cells.Journal of virology · 2016Article
- Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory.PloS one · 2016Article
- Strong Inference in Mathematical Modeling: A Method for Robust Science in the Twenty-First Century.Frontiers in microbiology · 2016Article
- HIV-1 CCR5 gene therapy will fail unless it is combined with a suicide gene.Scientific reports · 2015Article
- Article
- Within-host stochastic emergence dynamics of immune-escape mutants.PLoS computational biology · 2015Article
- Article
- Quantifying T lymphocyte turnover.Journal of theoretical biology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In theoretical ecology it is well known that the steady state expressions of the variables in a food chain crucially depend on the parity of the length of the chain. This poses a major problem for modeling real food webs because it is difficult to establish their true number of trophic levels, with sometimes rare predators and often rampant pathogens. Similar problems arise in the modeling of chronic viral infections. We review examples where seemingly general interpretations strongly depend on the number of levels in a model, and on its specific equations. This Perspective aims to open the discussion on this problem.
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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.