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Biomolecular Interaction Analysis Using an Optical Surface Plasmon Resonance Biosensor with a Marquardt Algorithm

机译:具有框架算法的光学表面等离子体共振生物传感器的生物分子相互作用分析

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This current paper presented the kinetic analysis and model building using the Marquardt algorithm based on Gauss-Newton iteration for biomolecular interaction. This algorithm for biomolecular interaction analysis of the optical surface plasmon resonance was applied to implement the nonlinear fitting of association and disassociation process of the receptor to ligand (or the antibody to antigen). Finally, the kinetic parameters were obtained from the fitting curve established by the Marquardt algorithm. The results show that the Marquardt algorithm does not only reduce the dependence of initial value to avoid the divergence but also can greatly reduce the iterative regression times. The correlation coefficient R-squared of the original curve formed by OriginPro and the fitting curves constructed using the Marquardt algorithm in association process and in disassociation process were 0.99158 and 0.99693, respectively. Correspondingly, the kinetic parameters and affinity constants were evaluated using the obtained data from the fitting results.
机译:本研究当前纸张使用基于Gauss-Newton迭代的Marquardt算法进行了动力学分析和模型建筑,以进行生物分子相互作用。该用于光学表面等离子体共振的生物分子相互作用分析算法用于实现受体与配体(或抗原抗体)的关联和脱离过程的非线性拟合。最后,从MarquardT算法建立的拟合曲线获得动力学参数。结果表明,Marquardt算法不仅降低了初始值的依赖性,以避免发散,而且可以大大降低迭代回归时间。由AroundPro形成的原始曲线的相关系数R和使用在关联过程和解剖过程中使用的Marquardt算法构造的拟合曲线分别为0.99158和0.99693。相应地,使用来自拟合结果的获得的数据评估动力学参数和亲和力常数。

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