ArticleInterface focus2013
Convergence in parameters and predictions using computational experimental design.
Article in Interface focus, 2013. 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.
- NLoed: A Python Package for Nonlinear Optimal Experimental Design in Systems Biology.ACS synthetic biology · 2022Article
- Algebra, Geometry and Topology of ERK Kinetics.Bulletin of mathematical biology · 2022Article
- Analysis of sloppiness in model simulations: Unveiling parameter uncertainty when mathematical models are fitted to data.Science advances · 2022Article
- Parameter estimation and uncertainty quantification using information geometry.Journal of the Royal Society, Interface · 2022Review
- GAMES: A Dynamic Model Development Workflow for Rigorous Characterization of Synthetic Genetic Systems.ACS synthetic biology · 2022Article
- A protocol for dynamic model calibration.Briefings in bioinformatics · 2022Article
- Article
- Cell-machine interfaces for characterizing gene regulatory network dynamics.Current opinion in systems biology · 2019Article
- Prediction of Optimal Drug Schedules for Controlling Autophagy.Scientific reports · 2019Article
- Comprehensive Review of Models and Methods for Inferences in Bio-Chemical Reaction Networks.Frontiers in genetics · 2019Review
- Article
- Studying Cellular Signal Transduction with OMIC Technologies.Journal of molecular biology · 2015Review
- A Bayesian active learning strategy for sequential experimental design in systems biology.BMC systems biology · 2014Article
- Reverse engineering and identification in systems biology: strategies, perspectives and challenges.Journal of the Royal Society, Interface · 2014Review
- Designing experiments to understand the variability in biochemical reaction networks.Journal of the Royal Society, Interface · 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
3 authors.
Funding
Abstract
Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.
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.