INFORMATION PROCESSING APPARATUS, FLOW CYTOMETER SYSTEM, SORTING SYSTEM, AND INFORMATION PROCESSING METHOD

Abstract

An information processing apparatus including a dimension compression section that generates dimension-compressed data for input data on the basis of a learning model generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.

Description

Claims

1. An information processing apparatus comprising a dimension compression section that generates dimension-compressed data for input data on a basis of a learning model generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.

2. The information processing apparatus according to claim 1, wherein the learning model includes a network structure and weighting of the neural network including the input layer, at least one or more intermediate layers, and the output layer, the at least one or more intermediate layers each having a smaller number of nodes than a number of nodes of the input layer, the output layer having a same number of nodes as the number of nodes of the input layer.

3. The information processing apparatus according to claim 2, wherein the learning model includes an autoencoder.

4. The information processing apparatus according to claim 3, wherein the learning model performs no stochastic process.

5. The information processing apparatus according to claim 2, wherein the dimension-compressed data includes output data from the respective nodes of the intermediate layers.

6. The information processing apparatus according to claim 1, wherein the dimension-compressed data includes data subjected to dimension compression into three-dimensional data or lower-dimensional data.

7. The information processing apparatus according to claim 1, wherein the input data includes multi-dimensional data acquired from the biologically derived substance.

8. The information processing apparatus according to claim 7, wherein the input data includes data that is same as data used to generate the learning model.

9. The information processing apparatus according to claim 7, wherein the input data includes data that is different from data used to generate the learning model.

10. The information processing apparatus according to claim 7, wherein the input data includes multi-dimensional data acquired from a biologically derived particle, the multi-dimensional data including fluorescence intensity or scattered light intensity.

11. The information processing apparatus according to claim 10, further comprising a sorting control section that controls a sorting section, the sorting section sorting, on a basis of the dimension-compressed data, the biologically derived particle from which the input data is acquired.

12. The information processing apparatus according to claim 1, further comprising a learning section that generates the learning model.

13. A flow cytometer system comprising: a laser light source that irradiates a biologically derived particle with light, the biologically derived particle flowing in a flow path;a photodetector that detects light from the biologically derived particle; anda dimension compression section that generates dimension-compressed data for measurement data on a basis of a learning model, the measurement data being obtained by the photodetector, wherein the learning model is generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.

14. The flow cytometer system according to claim 13, wherein the biologically derived substance includes a particle that is labeled with a same fluorescent dye as a fluorescent dye of the biologically derived particle.

15. A sorting system comprising: a laser light source that irradiates a biologically derived particle with light, the biologically derived particle flowing in a flow path;a photodetector that detects light from the biologically derived particle;a dimension compression section that generates dimension-compressed data for measurement data on a basis of a learning model, the measurement data being obtained by the photodetector; anda sorting section that sorts the biologically derived particle on a basis of the dimension-compressed data, wherein the learning model is generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.

16. The sorting system according to claim 15, wherein data used to generate the learning data includes multi-dimensional data acquired from the biologically derived particle in advance.

17. An information processing method comprising generating, by an arithmetic processing device, dimension-compressed data for input data on a basis of a learning model generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.