ArticleBiological cybernetics2019
Parameter subset selection techniques for problems in mathematical biology.
Article in Biological cybernetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Parameter identifiability of a neuroendocrine-inflammatory model across experimental designs.ArXiv · 2026Article
- Developing a Digital Twin of the Cardiopulmonary System in a Mouse: Inferring Hemodynamics from Sparse Measurements.Annals of biomedical engineering · 2026Article
- Multiscale computational modeling of the cardiopulmonary consequences of postnatal hyperoxia with implications for preterm-born children.Biomechanics and modeling in mechanobiology · 2026Article
- Multiscale Computational Modeling of the Cardiopulmonary Consequences of Postnatal Hyperoxia with Implications for Preterm Born Children.bioRxiv : the preprint server for biology · 2025Article
- Parameter selection and optimization of a computational network model of blood flow in single-ventricle patients.Journal of the Royal Society, Interface · 2025Article
- The impact of experimental designs & system sloppiness on the personalisation process: A cardiovascular perspective.PloS one · 2025Article
- Guidelines for mechanistic modeling and analysis in cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2024Review
- Biventricular Interaction During Acute Left Ventricular Ischemia in Mice: A Combined In-Vivo and In-Silico Approach.Annals of biomedical engineering · 2023Article
- Biventricular interaction during acute left ventricular ischemia in mice: a combined in-vivo and in-silico approach.bioRxiv : the preprint server for biology · 2023Article
- An in-silico analysis of experimental designs to study ventricular function: A focus on the right ventricle.PLoS computational biology · 2022Article
- Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model.Journal of theoretical biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Patient-specific models for diagnostics and treatment planning require reliable parameter estimation and model predictions. Mathematical models of physiological systems are often formulated as systems of nonlinear ordinary differential equations with many parameters and few options for measuring all state variables. Consequently, it can be difficult to determine which parameters can reliably be estimated from available data. This investigation highlights pitfalls associated with practical parameter identifiability and subset selection. The latter refer to the process associated with selecting a subset of parameters that can be identified uniquely by parameter estimation protocols. The methods will be demonstrated using five examples of increasing complexity, as well as with patient-specific model predicting arterial blood pressure. This study demonstrates that methods based on local sensitivities are preferable in terms of computational cost and model fit when good initial parameter values are available, but that global methods should be considered when initial parameter value is not known or poorly understood. For global sensitivity analysis, Morris screening provides results in terms of parameter sensitivity ranking at a much lower computational cost.
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.