A method is proposed for processing large data sets of fluorescence decay kinetic curves using data mining algorithms to determine the parameters of biophysical and optical processes in molecular systems. The idea of this method involves breaking the initial set of fluorescence decay curves into clusters in terms of some degree of similarity, finding medoids of the clusters, applying a dimensionality reduction method to the data and imaging the experimental data in two- and three-dimensional space, and analyzing the decay curves of the medoids using analytic or simulation models. The applicability of the method is examined for the example of analyzing sets of data representing systems of fluorophores. This method requires substantially less time and calculations of the analytic approximation functions, while the accuracy of the estimated parameters is higher than in the classical approach.

中文翻译：

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数据挖掘算法处理荧光衰减动力学曲线的方法

提出了一种使用数据挖掘算法处理荧光衰减动力学曲线的大型数据集以确定分子系统中生物物理和光学过程参数的方法。该方法的思想涉及在某种程度的相似度上将荧光衰减曲线的初始集合分解为簇，找到簇的质心，对数据应用降维方法并对二维和三维实验数据进行成像空间，并使用解析或仿真模型分析类固醇的衰减曲线。以分析代表荧光团系统的数据集为例，检验了该方法的适用性。该方法所需的时间大大减少，并且无需计算解析近似函数，