Donghui Son1, Jaejik Kim2

  • 1Department of Statistics & Actuarial Science, Simon Fraser University, Burnaby, Canada.

概括

本研究引入了贝叶斯验证方法来评估动态系统的普通微分方程 (ODE) 模型. 它随着时间的推移量化模型偏差,提高生物网络的预测准确性.

相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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In the absence of...
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BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Protein Networks02:26

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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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