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September 21, 2022Science AdvancesOpen Access

The approach identifies stiff parameter combinations affecting model-data fit, reveals controlling mechanisms underlying the modeled system, and informs which parameters need prioritization in future experiments.

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Why the study?

In complex systems, the amount and quality of data are frequently low compared to the number of model parameters to be collectively estimated.

Population

Mathematical models in biochemistry, ecology, and cardiac electrophysiology

Design

Methodological modeling study

Authors

GMGloria M. Monsalve-BravoBLBrodie LawsonCDChristopher Drovandi

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Overview

Refines parameter sensitivity analysis in complex models; leaves open its adoption in cardiovascular research without validation.

Structured PICO

P
Population
Mathematical models in complex systems (applications in biochemistry, ecology, and cardiac electrophysiology)
I
Intervention
A comprehensive approach to assess the sensitivity of model outputs to changes in parameter values, constrained by prior beliefs and data
O
Outcome
Identification of stiff parameter combinations affecting model-data fit

Introduces a mathematical approach to identify key parameter combinations in complex models, aiding in parameter inference and experimental prioritization.

Cite This Study

Monsalve-Bravo et al. (2022) studied this question.

synapsesocial.com/papers/6a7cfad146e525e01ea567d5https://doi.org/10.1126/sciadv.abm5952
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