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CLASSIFICATION ANALYSIS METHOD, CLASSIFICATION ANALYSIS DEVICE, AND STORAGE MEDIUM FOR CLASSIFICATION ANALYSIS

机译:分类分析方法,分类分析装置和用于分类分析的存储介质

摘要

The present invention provides a classification analysis method, a classification analysis device, and a storage medium for classification analysis, which enable, with high accuracy, the classification analysis of particulate or molecular analytes. As a means for solving the problem, a data group of particle-passage detection signals is based which are detected by a nanopore device 8 in accordance with passage of subject particles through a through-hole 12. A feature value is obtained in advance which indicates the feature of the waveform of the pulse signals corresponding to the passage of the predetermined analyte and the feature value obtained in advance is set as the learning data for the machine learning. The feature value obtained from the pulse signals of said analyzed data is set as a variable and the classification analysis on the predetermined analytes in the analyzed data can be performed by executing a classification analysis program due to the machine learning.
机译:本发明提供一种分类分析方法,分类分析装置和用于分类分析的存储介质,其能够高精度地对颗粒或分子分析物进行分类分析。作为解决该问题的手段,基于粒子通过检测信号的数据组,该信号通过纳米孔装置 8 根据被检体通过贯通孔 12的情况进行检测。 。预先获得表示与预定分析物的通过相对应的脉冲信号的波形的特征的特征值,并且将预先获得的特征值设置为用于机器学习的学习数据。从所述分析数据的脉冲信号获得的特征值被设置为变量,并且由于机器学习,可以通过执行分类分析程序来对分析数据中的预定分析物进行分类分析。

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