ArticleMolecular bioSystems2010
Sloppy models, parameter uncertainty, and the role of experimental design.
Article in Molecular bioSystems, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 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
55 citing papers in PubMed.
- A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations.PLoS computational biology · 2025Article
- The impact of experimental designs & system sloppiness on the personalisation process: A cardiovascular perspective.PloS one · 2025Article
- Global and local identifiability analysis of a nonlinear biphasic constitutive model in confined compression.Journal of the Royal Society, Interface · 2024Article
- 3D chromatin architecture, BRD4, and Mediator have distinct roles in regulating genome-wide transcriptional bursting and gene network.Science advances · 2024Article
- Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3DBiophysics reviews · 2024Review
- Kinetic Modeling and Parameter Estimation of a Prebiotic Peptide Reaction Network.Journal of molecular evolution · 2023Article
- Sloppiness: Fundamental study, new formalism and its application in model assessment.PloS one · 2023Article
- Information geometry for multiparameter models: new perspectives on the origin of simplicity.Reports on progress in physics. Physical Society (Great Britain) · 2022Review
- 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
- Ion channel model reduction using manifold boundaries.Journal of the Royal Society, Interface · 2022Article
- GAMES: A Dynamic Model Development Workflow for Rigorous Characterization of Synthetic Genetic Systems.ACS synthetic biology · 2022Article
- MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY.Current opinion in systems biology · 2021Article
- Article
- Accelerated knowledge discovery from omics data by optimal experimental design.Nature communications · 2020Article
- Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Computing Bayes factors for evidence-accumulation models using Warp-III bridge sampling.Behavior research methods · 2020Article
- Optimal Design of Single-Cell Experiments within Temporally Fluctuating Environments.Complexity · 2020Article
- Computational optimization of associative learning experiments.PLoS computational biology · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
Computational models are increasingly used to understand and predict complex biological phenomena. These models contain many unknown parameters, at least some of which are difficult to measure directly, and instead are estimated by fitting to time-course data. Previous work has suggested that even with precise data sets, many parameters are unknowable by trajectory measurements. We examined this question in the context of a pathway model of epidermal growth factor (EGF) and neuronal growth factor (NGF) signaling. Computationally, we examined a palette of experimental perturbations that included different doses of EGF and NGF as well as single and multiple gene knockdowns and overexpressions. While no single experiment could accurately estimate all of the parameters, experimental design methodology identified a set of five complementary experiments that could. These results suggest optimism for the prospects for calibrating even large models, that the success of parameter estimation is intimately linked to the experimental perturbations used, and that experimental design methodology is important for parameter fitting of biological models and likely for the accuracy that can be expected from them.
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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.