公开(公告)号：US20200251184A1

公开(公告)日：2020-08-06

申请号：US16470140

申请日：2017-12-12

Applicant: Osaka University

Inventor： Takashi WASHIO ,  Tomoji KAWAI ,  Masateru TANIGUCHI ,  Makusu TSUTSUI ,  Kazumichi YOKOTA ,  Akira ISHI ,  Takeshi YOSHIDA

IPC: G16B40/10 ,  G06K9/62 ,  G06N20/10 ,  G06F17/18 ,  G01N27/327 ,  G01N33/487

Abstract: 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.

公开(公告)号：US20190257787A1

公开(公告)日：2019-08-22

申请号：US16065633

申请日：2016-12-19

Applicant: Osaka University

Inventor： Takashi WASHIO ,  Tomoji KAWAI ,  Masateru TANIGUCHI ,  Makusu TSUTSUI ,  Kazumichi YOKOTA ,  Akira ISHI ,  Takeshi YOSHIDA

IPC: G01N27/447 ,  G01N33/487

Abstract: The present invention provides a number analyzing method, a number analyzing device, and a storage medium for number analysis, which enable, with high accuracy, analysis of the number or number distribution of particulate or molecular analytes according to the kinds of the analytes. A computer control program is executed on the basis of a data group of particle-passage detection signals which are detected by a nanopore device (8) in accordance with passage of subject particles through a through-hole (12). Also, a particle type distribution estimating program, which is a number deriving means, is executed, to estimate probability density on the basis of a data group based on feature values indicating feature of the waveforms of pulse signals which correspond to the passage of particles and which are obtained as the particle-passage detection signals. Thus, the number of particles can be derived for each particle type.