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Summary Ordinary differential equation (ODE)-based modeling is a powerful tool in the design and characterization of synthetic gene circuits. Despite its popularity, identifying the model parameters based off experimental measurement is a nontrivial task. In this study, we leverage cell-free experimental measurement of two RNA-based regulators to investigate the impact and the incorporation of measurement variance in the pair-wise squared error objective function used for ODE-model parameterization. Our findings suggest that while unweighted objective function and weighting by the inverse variance can provide reasonably accurate parameter estimation, weighing the objective function with the inverse stabilized variance could further improve the parameterization, by also capturing the system variance with a mitigated prediction variance.
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Measures of Variance on Windowed Gaussian Processes
Abstract The variance and fractional variance on a fixed time window (variously known as “rms percent” or “modulation index”) are commonly used to characterize the variability of astronomical sources. We summarize properties of this statistic for a Gaussian process.
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- PAR ID:
- 10387834
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- Research Notes of the AAS
- Volume:
- 6
- Issue:
- 12
- ISSN:
- 2515-5172
- Format(s):
- Medium: X Size: Article No. 279
- Size(s):
- Article No. 279
- Sponsoring Org:
- National Science Foundation
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