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Local and global sensitivity analysis of PCR kinetic model

Local and global sensitivity analysis of PCR kinetic model
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摘要 A mathematical model of polymerase chain reaction (PCR) containing uncertain and time-varying parameters has become important for model-based guidance experiment design. In this study, the local and global sensitivity analyses were conducted to identify that the responses of PCR process vary with their parameters of initial reactant concentrations and rate constants. Our results showed that the template concentration in initial reactant concentrations had the largest effect on DNA amplification yield. The rate constant characteristics showed that the local sensitivity basically determined the specific reactions; and the global sensitivity, the non-specific reactions. Our work should be helpful for optimizing PCR experimental conditions, and determining the PCR parameter sensitivities. A mathematical model of polymerase chain reaction (PCR) containing uncertain and time-varying parameters has become important for model-based guidance experiment design. In this study, the local and global sensitivity analyses were conducted to identify that the responses of PCR process vary with their parameters of initial reactant concentrations and rate constants. Our results showed that the template concentration in initial reactant concentrations had the largest effect on DNA amplification yield. The rate constant characteristics showed that the local sensitivity basically determined the specific reactions; and the global sensitivity, the non-specific reactions. Our work should be helpful for optimizing PCR experimental conditions, and determining the PCR parameter sensitivities.
出处 《Nuclear Science and Techniques》 SCIE CAS CSCD 2012年第2期124-128,共5页 核技术(英文)
基金 Supported by the Shanghai Municipal Commission for Science and Technology (09395811700) National Basic Research Program of China (2007CB936000)
关键词 敏感性分析 PCR 动力学模型 聚合酶链反应 反应速率常数 反应物浓度 非特异性反应 变参数模型 Polymerase chain reaction, Optimization, mathematical model, Sensitivity analysis
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