Estimating and Assessing Differential Equation Models with Time-Course Data Article Swipe

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Samuel W. K. Wong , Shihao Yang , S. C. Kou ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1021/acs.jpcb.2c08932

Ordinary differential equation (ODE) models are widely used to describe chemical or biological processes. This Article considers the estimation and assessment of such models on the basis of time-course data. Due to experimental limitations, time-course data are often noisy, and some components of the system may not be observed. Furthermore, the computational demands of numerical integration have hindered the widespread adoption of time-course analysis using ODEs. To address these challenges, we explore the efficacy of the recently developed MAGI (MAnifold-constrained Gaussian process Inference) method for ODE inference. First, via a range of examples we show that MAGI is capable of inferring the parameters and system trajectories, including unobserved components, with appropriate uncertainty quantification. Second, we illustrate how MAGI can be used to assess and select different ODE models with time-course data based on MAGI's efficient computation of model predictions. Overall, we believe MAGI is a useful method for the analysis of time-course data in the context of ODE models, which bypasses the need for any numerical integration.

Related Topics

Differential Equation

Mathematics

Gaussian Function

Artificial Intelligence

Composite Material

Paleontology

Biology

Mathematical Analysis

Physics

Materials Science

Quantum Mechanics

Concepts

Ode Ordinary differential equation Inference Context (archaeology) Computer science Computation Range (aeronautics) Numerical integration Process (computing) Gaussian process Algorithm Applied mathematics Differential equation Mathematics Gaussian Artificial intelligence Composite material Paleontology Operating system Biology Mathematical analysis Physics Materials science Quantum mechanics

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Type: article
Language: en
Landing Page: https://doi.org/10.1021/acs.jpcb.2c08932
OA Status: green
Cited By: 4
References: 69
Related Works: 10
OpenAlex ID: https://openalex.org/W4323657381

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DOI: https://doi.org/10.1021/acs.jpcb.2c08932

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Title: Estimating and Assessing Differential Equation Models with Time-Course Data

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Language: en

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Publication year: 2023

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Publication date: 2023-03-09

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Authors: Samuel W. K. Wong, Shihao Yang, S. C. Kou

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Landing page: https://doi.org/10.1021/acs.jpcb.2c08932

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Concepts: Ode, Ordinary differential equation, Inference, Context (archaeology), Computer science, Computation, Range (aeronautics), Numerical integration, Process (computing), Gaussian process, Algorithm, Applied mathematics, Differential equation, Mathematics, Gaussian, Artificial intelligence, Composite material, Paleontology, Operating system, Biology, Mathematical analysis, Physics, Materials science, Quantum mechanics

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Cited by: 4

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publication_year	2023
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