Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable.
Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable.
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DOI：
10.3389/fbioe.2015.00209
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发表时间：
2015
影响因子：
5.7
通讯作者：
Seemann G
中科院分区：
文献类型：
--
作者：
Loewe A;Wilhelms M;Schmid J;Krause MJ;Fischer F;Thomas D;Scholz EP;Dössel O;Seemann G
心脏电生理学的计算模型提供了对心律失常发生的洞察，并在过去几年为量身定做的治疗铺平了道路。然而，为了在未来的研究中充分利用计算机模型，这些模型需要进行调整，以反映病理、基因改变或药物效应。一种常见的方法是保持已建立的模型的结构不变，并估计一组参数的值。今天的高通量膜片钳数据采集方法需要健壮、无监督的算法来准确可靠地估计参数。在这项工作中，评估了两类优化方法：基于梯度的信赖域反射粒子群算法和无导数粒子群算法。使用合成输入数据和来自Courtemmane等人的不同离子电流公式。通过建立人心房肌细胞电生理模型，我们发现这两种方案都不能满足所有的要求。这两种算法的顺序组合确实在一定程度上提高了性能，但并不令人满意。因此，我们提出了一种新的混合方法，在每次迭代中将两种算法结合起来。这种混合方法使用存在基本真实参数集的合成输入数据产生非常准确的估计，并且对初始猜测的依赖性最小。当应用于测量数据时，混合方法产生了最好的拟合，同样具有最小的差异。使用所提出的算法，一次运行就足以估计参数。在准确性和稳健性方面优于其他被调查算法的程度取决于电流的类型。与非混合方法相比，该方法对任意信噪比的数据是最优的。这项工作中提出的混合算法提供了一个重要的工具，可以将实验数据准确而稳健地整合到计算模型中，从而能够在更高的整合水平上评估离子通道水平变化往往不直观的后果。
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration.
影响因子：
--
作者：
Tøndel K;Niederer SA;Land S;Smith NP
通讯作者：
Smith NP