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Parameter estimation method for improper fractional models and its application to molecular biological systems

机译:不正确分数模型的参数估计方法及其在分子生物学系统中的应用

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Derived from biochemical principles, molecular biological systems can be described by a group of differential equations. Generally these differential equations contain fractional functions plus polynomials (which we call improper fractional model) as reaction rates. As a result, molecular biological systems are nonlinear in both parameters and states. It is well known that it is challenging to estimate parameters nonlinear in a model. However, in fractional functions both the denominator and numerator are linear in the parameters while polynomials are also linear in parameters. Based on this observation, we develop an iterative linear least squares method for estimating parameters in biological systems modeled by improper fractional functions. The basic idea is to transfer optimizing a nonlinear least squares objective function into iteratively solving a sequence of linear least squares problems. The developed method is applied to the estimation of parameters in a metabolism system. The simulation results show the superior performance of the proposed method for estimating parameters in such molecular biological systems.
机译:源自生物化学原理的分子生物学系统可以用一组微分方程来描述。通常,这些微分方程包含分数函数和多项式(我们称为不正确的分数模型)作为反应速率。结果,分子生物学系统在参数和状态上都是非线性的。众所周知,在模型中估计非线性参数具有挑战性。但是,在分数函数中,分母和分子在参数中都是线性的,而多项式在参数中也是线性的。基于此观察结果,我们开发了一种迭代线性最小二乘法,用于估计由不正确的分数函数建模的生物系统中的参数。基本思想是将优化非线性最小二乘目标函数转换为迭代求解一系列线性最小二乘问题。所开发的方法被应用于代谢系统中参数的估计。仿真结果表明,该方法在此类分子生物学系统中估计参数具有优越的性能。

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