Information processing method, information processing device, and information processing system

Abstract

The present technology relates to an information processing method, information processing device, and information processing system that make it possible to easily analyze experimental data including a plurality of pieces of particle data. The information processing method involves: setting, by means of an information processing device on the basis of a reference document, at least one among an analysis algorithm or an analysis parameter used for analyzing experimental data including a plurality of pieces of particle data based on light from each of a plurality of particles; and analyzing, by means of the information processing device, the experimental data by using the set analysis algorithm or analysis parameter. The present technology can be applied to flow cytometry, for example.

Description

Information processing method, information processing device, and information processing system

[0001] The present technology relates to an information processing method, an information processing device, and an information processing system.

[0002] In recent years, with the increasing number of colors in FCM (flow cytometers), the amount of data has increased, making the analysis of FCM data (hereinafter referred to as FCM data) more complex. In response to this, dimensionality reduction and clustering, for example, have been used to facilitate the analysis of FCM data.

[0003] Furthermore, a system has been proposed in which FCM data is analyzed through dialogue with a user using analysis commands (see, for example, Patent Document 1).

[0004] International Publication No. 2022 / 080102

[0005] However, even when considering dimensionality reduction alone, there are various algorithms available, such as t-SNE (t-Distributed Stochastic Neighbor Embedding), UMAP (Uniform Manifold Approximation and Projection), and AutoEncoder. Furthermore, each algorithm has its own unique parameters that need to be adjusted. Therefore, in order to properly analyze FCM data, knowledge of the analysis algorithms is required.

[0006] The present technology has been developed in light of these circumstances, and makes it possible to easily analyze experimental data including data on a plurality of particles, such as FCM data.

[0007] An information processing method according to a first aspect of the present technology includes an information processing device setting, based on a reference document, at least one of an analysis algorithm or an analysis parameter used to analyze experimental data including a plurality of particle data based on light from each of a plurality of particles, and analyzing the experimental data using the analysis algorithm and the analysis parameter.

[0008] An information processing device according to a first aspect of the present technology includes an analysis method setting unit that sets, based on a reference document, at least one of an analysis algorithm or an analysis parameter used to analyze experimental data including a plurality of particle data based on light from each of a plurality of particles, and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameter.

[0009] An information processing system according to a second aspect of the present technology includes a detection unit that detects light from each of a plurality of particles, and an information processing unit, wherein the information processing unit includes an analysis method setting unit that sets, based on a reference document, at least one of an analysis algorithm or an analysis parameter used to analyze experimental data including a plurality of particle data based on light from each of the plurality of particles, and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameter.

[0010] In a first aspect of the present technology, at least one of an analysis algorithm or analysis parameters used to analyze experimental data including a plurality of particle data based on light from each of a plurality of particles is set based on a reference document, and the experimental data is analyzed using the analysis algorithm and the analysis parameters.

[0011] In a second aspect of the present technology, light from each of a plurality of particles is detected, and at least one of an analysis algorithm or analysis parameters used to analyze experimental data including a plurality of particle data based on the light from each of the plurality of particles is set based on a reference document, and the experimental data is analyzed using the analysis algorithm and the analysis parameters.

[0012] FIG. 1 is a block diagram showing an example of the configuration of an information processing system. FIG. 2 is a block diagram showing an example of the configuration of a biological sample analyzer. FIG. 3 is a block diagram showing an example of the configuration of an information processing unit. FIG. 4 is a diagram showing an example of the data structure of a literature DB. FIG. 5 is a flowchart for explaining the flow of an experiment. FIG. 6 is a flowchart for explaining analysis and editing processing. FIG. 7 is a flowchart for explaining details of analysis processing. FIG. 8 is a diagram showing an example of presentation of analysis results of experimental data. FIG. 9 is a flowchart for explaining details of additional analysis processing. FIG. 10 is a sequence diagram for explaining a specific example of a method for correcting analysis results. FIG. 11 is a flowchart for explaining details of editing processing. FIG. 12 is a sequence diagram for explaining an example of input of difference information. FIG. 13 is a flowchart for explaining literature curation processing. FIG. 14 is a diagram showing an example of the configuration of a computer.

[0013] Hereinafter, embodiments of the present technology will be described. The description will be made in the following order: 1. Embodiment 2. Modification 3. Other

[0014] <<1. Embodiment>> An embodiment of the present technology will be described with reference to FIGS. 1 to 13 .

[0015] <Configuration Example of Information Processing System> FIG. 1 shows a configuration example of an information processing system 1 to which the present technology is applied.

[0016] The information processing system 1 comprises biological sample analyzers 11-1 to 11-n, a server 12-1, and a server 12-2.

[0017] The biological sample analyzers 11-1 to 11-m and the server 12-2 are connected via a network (not shown) and are owned by a single organization.

[0018] The organizational unit that owns biological sample analyzers 11-1 through 11-m and server 12-2 is not particularly limited. For example, the organization may be a single company, school, organization, etc., or a department of a company, school, organization, etc.

[0019] The biological sample analyzers 11-m+1 to 11-n, the server 12-1, and the server 12-2 are connected via a network (not shown).

[0020] Hereinafter, when there is no need to distinguish between the biological sample analyzers 11-1 to 11-n, they will simply be referred to as the biological sample analyzers 11. Hereinafter, when there is no need to distinguish between the servers 12-1 and 12-2, they will simply be referred to as the servers 12.

[0021] The biological sample analyzer 11 is composed of, for example, a flow cytometer and an imaging cytometer.

[0022] The server 12, for example, controls each biological sample analyzer 11. The server 12 manages and processes, for example, the data and programs used by each biological sample analyzer 11, as well as the data obtained by processing each biological sample analyzer 11.

[0023] Furthermore, the server 12-1 prevents, for example, data obtained by the biological sample analyzer 11 within an organization from leaking outside the organization.

[0024] The number of servers 12 and organizations is not limited to the example shown in this drawing. Also, for example, one organization may own multiple servers 12.

[0025] <Configuration Example of Biological Sample Analyzer 11> FIG. 2 shows a configuration example of the biological sample analyzer 11 of FIG.

[0026] The biological sample analyzer 11 includes a light irradiation unit 111 that irradiates light onto the biological sample S flowing through the flow path C, a detection unit 112 that detects light generated by irradiating the biological sample S with light, and an information processing unit 113 that processes information related to the light detected by the detection unit 112. Examples of the biological sample analyzer 11 include a flow cytometer and an imaging cytometer. The biological sample analyzer 11 may also include a fractionation unit 114 that separates specific biological particles P from within the biological sample. An example of a biological sample analyzer 11 that includes a fractionation unit 114 is a cell sorter.

[0027] (Biological Sample) The biological sample S may be a liquid sample containing biological particles. The biological particles may be, for example, cells or non-cellular biological particles. The cells may be living cells, and more specific examples include blood cells such as red blood cells and white blood cells, and reproductive cells such as sperm and fertilized eggs. The cells may be directly collected from a specimen such as whole blood, or may be cultured cells obtained after culturing. Examples of the non-cellular biological particles include extracellular vesicles, particularly exosomes and microvesicles.

[0028] The bioparticles may be labeled with one or more labeling substances (e.g., dyes (particularly fluorescent dyes) and fluorescent dye-labeled antibodies). For example, the bioparticles may be labeled (stained) with one or more types of fluorescent dyes. The labeling of the bioparticles with fluorescent dyes may be performed by known techniques. Specifically, when the bioparticles are cells, the cells to be measured can be labeled with the fluorescent dye by mixing a fluorescently labeled antibody that selectively binds to an antigen present on the cell surface with the cells to be measured and allowing the fluorescently labeled antibody to bind to the antigen on the cell surface. Alternatively, the cells to be measured can be labeled with the fluorescent dye by mixing a fluorescent dye that is selectively taken up by specific cells with the cells to be measured.

[0029] A fluorescently labeled antibody is an antibody to which a fluorescent dye is bound as a label. The fluorescently labeled antibody may be one in which the fluorescent dye is directly bound to the antibody. Alternatively, the fluorescently labeled antibody may be one in which an avidin-bound fluorescent dye is bound to a biotin-labeled antibody via the avidin-biodin reaction. Note that either a polyclonal antibody or a monoclonal antibody can be used as the antibody.

[0030] The fluorescent dye for labeling cells is not particularly limited, and at least one known dye used for staining cells or the like can be used. For example, fluorescent dyes include phycoerythrin (PE), fluorescein isothiocyanate (FITC), PE-Cy5, PE-Cy7, PE-Texas Red (registered trademark), allophycocyanin (APC), APC-Cy7, ethidium bromide, propidium iodide, Hoechst (registered trademark) 33258, Hoechst (registered trademark) 33342, DAPI (4',6-diamidino-2-phenylindole), acridine orange, chromomycin, mithramycin, olivomycin, pyronin Y, thiazole orange, rhodamine 101, isothiocyanate, BCECF, BCECF-AM, C. Examples of fluorescent dyes that can be used include SNARF-1, C.SNARF-1-AMA, aequorin, Indo-1, Indo-1-AM, Fluo-3, Fluo-3-AM, Fura-2, Fura-2-AM, oxonol, Texas Red (registered trademark), rhodamine 123, 10-N-nony-acridine orange, fluorescein, fluorescein diacetate, carboxyfluorescein, carboxyfluorescein diacetate, carboxydichlorofluorescein, and carboxydichlorofluorescein diacetate. Derivatives of the above-mentioned fluorescent dyes can also be used.

[0031] (Flow Channel) The flow channel C is configured to allow the biological sample S to flow. In particular, the flow channel C can be configured to form a flow in which biological particles contained in the biological sample are aligned in a substantially straight line. The flow channel structure including the flow channel C may be designed to form a laminar flow. In particular, the flow channel structure is designed to form a laminar flow in which the flow of the biological sample (sample flow) is surrounded by the flow of sheath liquid. The design of the flow channel structure may be appropriately selected by those skilled in the art, and a known design may be adopted. The flow channel C may be formed in a flow channel structure such as a microchip (a chip having flow channels on the order of micrometers) or a flow cell. The width of the flow channel C may be 1 mm or less, particularly 10 μm or more and 1 mm or less. The flow channel C and the flow channel structure including it may be formed from a material such as plastic or glass.

[0032] The biological sample analyzer of the present disclosure is configured so that light from light irradiation unit 111 is irradiated onto the biological sample flowing within flow path C, particularly onto biological particles within the biological sample. The biological sample analyzer of the present disclosure may be configured so that the interrogation point of light on the biological sample is within the flow path structure in which flow path C is formed, or so that the interrogation point of light is outside the flow path structure. An example of the former is a configuration in which the light is irradiated onto flow path C within a microchip or flow cell. In the latter, the light may be irradiated onto biological particles after they have left the flow path structure (particularly its nozzle portion), such as a jet-in-air flow cytometer.

[0033] (Light Irradiation Unit) The light irradiation unit 111 includes a light source unit that emits light and a light-guiding optical system that guides the light to an irradiation point. The light source unit includes one or more light sources. The type of light source is, for example, a laser light source or an LED. The wavelength of the light emitted from each light source may be any of ultraviolet light, visible light, and infrared light. The light-guiding optical system includes optical components such as a beam splitter group, a mirror group, or an optical fiber. The light-guiding optical system may also include a lens group for focusing light, such as an objective lens. There may be one or more irradiation points where the light intersects with the biological sample. The light irradiation unit 111 may be configured to focus light irradiated from one or more different light sources to one irradiation point.

[0034] (Detection Unit) The detection unit 112 includes at least one photodetector that detects light generated by irradiating the bioparticles with light. The detected light is, for example, fluorescence or scattered light (e.g., one or more of forward scattered light, back scattered light, and side scattered light). Each photodetector includes one or more light-receiving elements, for example, a photodetector array. Each photodetector may include one or more photomultiplier tubes (PMTs) and / or photodiodes such as APDs and MPPCs as light-receiving elements. The photodetector includes, for example, a PMT array in which multiple PMTs are arranged in a one-dimensional direction. The detection unit 112 may also include an imaging element such as a CCD or CMOS. The detection unit 112 can acquire images of the bioparticles (e.g., bright-field images, dark-field images, and fluorescence images) using the imaging element.

[0035] The detection unit 112 includes a detection optical system that allows light of a predetermined detection wavelength to reach a corresponding photodetector. The detection optical system includes a spectroscopic unit such as a prism or a diffraction grating, or a wavelength separation unit such as a dichroic mirror or an optical filter. The detection optical system is configured to, for example, disperse light generated by irradiating bioparticles with light, and detect the dispersed light using a plurality of photodetectors, the number of which is greater than the number of fluorescent dyes with which the bioparticles are labeled. A flow cytometer that includes such a detection optical system is called a spectral flow cytometer. The detection optical system is also configured to, for example, separate light corresponding to the fluorescent wavelength range of a specific fluorescent dye from the light generated by irradiating bioparticles with light, and detect the separated light using a corresponding photodetector.

[0036] The detection unit 112 may also include a signal processing unit that converts the electrical signal obtained by the photodetector into a digital signal. The signal processing unit may include an A / D converter as a device that performs the conversion. The digital signal obtained by the conversion by the signal processing unit may be transmitted to the information processing unit 113. The digital signal may be handled by the information processing unit 113 as data related to light (hereinafter also referred to as "light data"). The light data may be light data including, for example, fluorescent light data. More specifically, the light data may be light intensity data, and the light intensity may be light intensity data of light including fluorescent light (which may include feature quantities such as area, height, and width).

[0037] (Information Processing Unit) The information processing unit 113 includes, for example, a processing unit that processes various data (e.g., optical data) and a storage unit that stores various data. When the processing unit acquires optical data corresponding to a fluorescent dye from the detection unit 112, the processing unit may perform fluorescence spillover correction (compensation processing) on ​​the light intensity data. Furthermore, in the case of a spectral flow cytometer, the processing unit performs fluorescence separation processing on the optical data to acquire light intensity data corresponding to the fluorescent dye. The fluorescence separation processing may be performed, for example, according to the unmixing method described in Japanese Patent Application Laid-Open No. 2011-232259. When the detection unit 112 includes an image sensor, the processing unit may acquire morphological information of bioparticles based on images acquired by the image sensor. The storage unit may be configured to store the acquired optical data. The storage unit may further be configured to store spectral reference data used in the unmixing processing.

[0038] If the biological sample analyzer 11 includes a fractionating unit 114 (described below), the information processing unit 113 can determine whether to fractionate the biological particles based on the optical data and / or morphological information. The information processing unit 113 then controls the fractionating unit 114 based on the result of this determination, and the fractionating unit 114 can collect the biological particles.

[0039] The information processing unit 113 may be configured to output various types of data (e.g., optical data and images). For example, the information processing unit 113 may output various types of data (e.g., two-dimensional plots, spectral plots, etc.) generated based on the optical data. The information processing unit 113 may also be configured to accept input of various types of data, such as accepting gating processing on a plot by a user. The information processing unit 113 may include an output unit (e.g., a display, etc.) or an input unit (e.g., a keyboard, etc.) for executing the output or input.

[0040] The information processing unit 113 may be configured as a general-purpose computer, for example, as an information processing device including a CPU, RAM, and ROM. The information processing unit 113 may be included in a housing that includes the light irradiation unit 111 and the detection unit 112, or may be located outside the housing. Furthermore, various processes or functions performed by the information processing unit 113 may be realized by a server computer or a cloud connected via a network.

[0041] (Sorting section) The sorting section 114 sorts the bioparticles according to the determination result by the information processing section 113. The sorting method may be a method of generating droplets containing bioparticles by vibration, applying an electric charge to the droplets to be sorted, and controlling the direction of travel of the droplets using electrodes. The sorting method may also be a method of controlling the direction of travel of the bioparticles within the flow path structure to perform sorting. The flow path structure is provided with, for example, a control mechanism using pressure (spray or suction) or electric charge. An example of such a flow path structure is a chip (for example, the chip described in JP 2020-76736 A) having a flow path structure in which a flow path C branches into a recovery flow path and a waste flow path downstream, and in which specific bioparticles are recovered into the recovery flow path.

[0042] <Configuration Example of Information Processing Unit 113> FIG. 3 shows a configuration example of the information processing unit 113 of the biological sample analyzer 11 of FIG.

[0043] The information processing unit 113 includes an input unit 201 , a control unit 202 , an output unit 203 , a communication unit 204 , an experiment data storage unit 205 , a literature DB (database) 206 , LLM (Large Language Models) 207 , and a storage unit 208 .

[0044] The input section 201 includes various input devices for inputting data to and operating the biological sample analyzer 11 .

[0045] The control unit 202 controls each unit of the information processing unit 113 and executes various processes. The control unit 202 includes an analysis and editing unit 221, an HMI (Human Machine Interface) control unit 222, and a curation unit 223.

[0046] The analysis and editing unit 221 analyzes the experiment data and edits the experiment report, which is a report on the experiment.

[0047] Here, the experimental data refers to data including a plurality of particle data based on light from each biological particle such as a cell, obtained by an experiment using the light irradiation unit 111 and the detection unit 112 (e.g., FCM). The particle data may be data obtained by performing various preprocessing steps on the optical data based on the light from each biological particle, or may be the optical data itself.

[0048] The analyzing and editing unit 221 includes a reference document setting unit 231 , an analysis method setting unit 232 , an analyzing unit 233 , and an editing unit 234 .

[0049] The reference document setting unit 231 sets reference documents to be used for analyzing experimental data and editing experimental reports from documents registered in the document DB 206, for example, based on conditions specified by the user. The reference document setting unit 231 supplies reference document information related to the reference documents to the analysis method setting unit 232, the editing unit 234, and the HMI control unit 222.

[0050] The analysis method setting unit 232 sets an analysis method for the experimental data. For example, the analysis method setting unit 232 sets an analysis algorithm, analysis parameters, conditions for correcting the analysis results of the experimental data, etc. The analysis method setting unit 232 includes an algorithm setting unit 241 and a parameter setting unit 242.

[0051] The algorithm setting unit 241 sets an analysis algorithm to be used for analyzing the experimental data based on, for example, conditions specified by a user or at least one of reference documents. The algorithm setting unit 241 supplies algorithm information related to the analysis algorithm to the analysis unit 233 and the HMI control unit 222.

[0052] The parameter setting unit 242 sets analysis parameters to be used in analyzing the experimental data based on, for example, conditions specified by the user or at least one of reference documents. The parameter setting unit 242 supplies parameter information related to the analysis parameters to the analysis unit 233 and the HMI control unit 222.

[0053] The analysis unit 233 stores the experimental data supplied from the detection unit 112 in the experimental data storage unit 205 as necessary. The analysis unit 233 analyzes the experimental data using an analysis algorithm set by an algorithm setting unit 241 and analysis parameters set by a parameter setting unit 242. The analysis unit 233 supplies analysis information relating to the analysis results of the experimental data to the editing unit 234 and the HMI control unit 222.

[0054] The editing unit 234 edits the experiment report. For example, the editing unit 234 uses the LLM 207 to generate an experiment report including the analysis results of the experiment data based on the reference literature, the analysis information, and difference information indicating the difference between the reference literature and the analysis results of the experiment data. The difference information is input by, for example, a user. The editing unit 234 supplies the experiment report to the HMI control unit 222 and stores it in the experiment data storage unit 205.

[0055] The curation unit 223 performs curation of various documents available on the Internet, etc., and updates the document DB 206 .

[0056] The HMI control unit 222 executes control of the HMI using the input unit 201 and the output unit 203. For example, the HMI control unit 222 recognizes instructions in natural language input by a user via the input unit 201, using the LLM 207. For example, the HMI control unit 222 controls the output of various information by the output unit 203 (for example, the results of analysis of experimental data, presentation of an experimental report, etc.).

[0057] The output unit 203 includes an output device capable of outputting various types of information, such as a display device such as a display, an audio output device such as a speaker, etc.

[0058] The communication unit 204 communicates with the server 12 and the like via a network (not shown).

[0059] The experiment data storage unit 205 stores the experiment data and the experiment report.

[0060] The literature DB 206 stores data related to literature used for analyzing experimental data and editing experimental reports. The types of literature are not particularly limited, and examples thereof include papers, books, reports, and articles.

[0061] FIG. 4 shows an example of the data structure of the document DB 206 .

[0062] The document DB 206 includes items such as ID, URL (Uniform Resource Locator), text, analysis algorithm, analysis parameters, experimental conditions, and experimental equipment.

[0063] The ID is an ID for identifying each document.

[0064] The URL indicates the URL of the website where the document is available.

[0065] The body of the document includes the content within the document (eg, text, figures, images, etc.).

[0066] The analysis algorithm indicates the analysis algorithm used in the literature to analyze the experimental data. If multiple analysis algorithms are used, multiple analysis algorithms may be registered.

[0067] The analysis parameters indicate the values ​​of each analysis parameter used in the analysis algorithm used to analyze the experimental data in the literature. If multiple values ​​are used for one analysis parameter, multiple values ​​may be registered.

[0068] The experimental conditions indicate the conditions used in the experiments in the literature, including, for example, information on the type of cells of the organism to be analyzed, the combination of the antigen to be analyzed (hereinafter referred to as the antigen marker) and the labeling substance (e.g., fluorescent dye, fluorescently labeled antibody, etc.), etc.

[0069] The experimental equipment includes information about the equipment used in the experiment in the document. For example, the experimental equipment includes the type, model name, model name, specifications, functions, etc. of the equipment used in the experiment. Note that although the experimental equipment is registered as a separate item from the experimental conditions, it constitutes part of the experimental conditions. Therefore, for example, information about the experimental equipment may be registered in the experimental conditions item.

[0070] The LLM 207 is used, for example, to edit experiment reports and recognize user instructions.

[0071] The learning method of the LLM 207 is not particularly limited.

[0072] The storage unit 208 stores various programs and data required for processing by the information processing unit 113 .

[0073] <Experimental Procedure> FIG. 5 shows an example of an experimental procedure using the biological sample analyzer 11.

[0074] In step S1, a hypothesis to be verified by an experiment is set.

[0075] In step S2, an experimental protocol is created. At this time, a panel design is constructed for the biological sample analyzer 11. In other words, an optimal combination of multiple labeling substances to be used in the experiment is designed.

[0076] In step S3, the equipment to be used in the experiment is set.

[0077] In step S4, the light generated by irradiating the bioparticles with light is measured, thereby obtaining experimental data.

[0078] In step S5, the experimental data is analyzed, for example, by a normal user, by machine learning, or by machine learning support for normal analysis.

[0079] In step S6, the experimental data is compiled, for example, into an experimental report including the results of analysis of the experimental data.

[0080] In step S7, the experiment data is shared. For example, the experiment report is made public on the server 12 or the experiment report is presented.

[0081] Note that this technology mainly targets the processes in steps S5 and S6.

[0082] <Analysis and Editing Process> Next, the analysis and editing process executed by the information processing unit 113 will be described with reference to the flowchart of FIG.

[0083] It is assumed that the experimental data to be analyzed has already been acquired and stored in the experimental data storage unit 205 .

[0084] In step S101, the information processing unit 113 executes an analysis process.

[0085] The analysis process will now be described in detail with reference to the flowchart of FIG.

[0086] In step S121, the analysis and editing unit 221 acquires analysis conditions.

[0087] For example, the user inputs analysis conditions for the experimental data to the information processing unit 113 via the input unit 201 .

[0088] The analysis conditions include, for example, at least the experimental conditions.

[0089] The experimental conditions indicate the conditions of the experiment conducted to obtain the experimental data to be analyzed. The experimental conditions include, for example, at least the following two pieces of data:

[0090] 1. The type of cell to be analyzed 2. The combination of antigen marker and labeling substance

[0091] The experimental conditions may also include, for example, the equipment used in the experiment (for example, the type of equipment, model name, model name, etc.).

[0092] The analysis conditions may also include, for example, reference literature and analysis algorithms.

[0093] Reference documents are documents that are referenced when analyzing experimental data and editing an experimental report. For example, documents that describe experiments similar to the experiment conducted by the user are used as reference documents. Note that reference documents may also be documents such as reports created by the user themselves. Reference documents are specified by, for example, the name of the document, the URL of the website where the document can be obtained, or a PMID (PubMed ID).

[0094] The analysis algorithm is an algorithm used to analyze the experimental data.

[0095] For example, if the analysis conditions entered by the user include a reference document, the reference document setting unit 231 sets the reference document as a document to be used in analyzing the experimental data and editing the experimental report. The reference document setting unit 231 supplies reference document information related to the set reference document to the analysis method setting unit 232 and the editing unit 234.

[0096] For example, if the analysis conditions input by the user include an analysis algorithm, the algorithm setting unit 241 sets the analysis algorithm to be used in analyzing the experimental data. The algorithm setting unit 241 supplies algorithm information related to the set analysis algorithm to the analysis unit 233.

[0097] In step S122, the reference document setting unit 231 determines whether or not a reference document has been specified. If the analysis conditions entered by the user do not include a reference document, the reference document setting unit 231 determines that no reference document has been specified, and the process proceeds to step S123.

[0098] In step S123, the information processing unit 113 sets reference documents. For example, the reference document setting unit 231 searches documents registered in the document DB 206 and identifies documents related to experiments similar to the experimental conditions specified by the user.

[0099] For example, the reference document setting unit 231 extracts reference document candidates from the document DB 206 in accordance with the following conditions 1 to 3.

[0100] Condition 1. The antigen marker is the same. Condition 2. The experimental equipment is the same. Condition 3. The labeling substance is the same.

[0101] For example, first, documents that satisfy condition 1 are extracted. If the number of extracted documents is equal to or less than a predetermined threshold, the extracted documents are selected as candidates for reference documents. If the number of extracted documents exceeds a predetermined threshold, documents that satisfy condition 2 are further extracted from among them. If the number of extracted documents is equal to or less than a predetermined threshold, the extracted documents are selected as candidates for reference documents. If the number of extracted documents exceeds a predetermined threshold, documents that satisfy condition 3 are further extracted from among them. Then, the extracted documents are selected as candidates for reference documents.

[0102] The reference document setting unit 231 supplies information indicating candidate reference documents to the HMI control unit 222 .

[0103] The output unit 203 presents candidates for reference documents under the control of the HMI control unit 222 .

[0104] In response to this, the user selects the reference document to be used from the presented candidate reference documents, and inputs information indicating the selection result to the information processing unit 113 via the input unit 201 .

[0105] The reference document setting unit 231 sets the document selected by the user as the reference document, and supplies reference document information relating to the set reference document to the analysis method setting unit 232 and the editing unit 234.

[0106] For example, the reference document setting unit 231 may automatically set as the reference document a document registered in the document DB 206 that describes an experiment under conditions most similar to the experimental conditions specified by the user.

[0107] Thereafter, the process proceeds to step S124.

[0108] On the other hand, in step S122, if the analysis conditions entered by the user include a reference document, the reference document setting unit 231 determines that a reference document has been specified, the processing of step S123 is skipped, and the processing proceeds to step S124.

[0109] In step S124, the algorithm setting unit 241 determines whether or not an analysis algorithm has been specified. If the analysis conditions entered by the user do not include an analysis algorithm, the algorithm setting unit 241 determines that an analysis algorithm has not been specified, and the process proceeds to step S125.

[0110] In step S125, the information processing unit 113 proposes an analysis algorithm. Specifically, the algorithm setting unit 241 acquires information about the analysis algorithm used in the reference document from the document DB 206. The algorithm setting unit 241 supplies the algorithm information about the analysis algorithm to the HMI control unit 222.

[0111] The output unit 203 presents the analysis algorithm included in the algorithm information under the control of the HMI control unit 222. For example, the output unit 203 displays a message such as "Dimensionality reduction UMAP is implemented in the reference document (for example, the specific document name is shown). Would you like to implement it?" or outputs a voice message.

[0112] If there are multiple candidate analysis algorithms, multiple analysis algorithms are presented.

[0113] In step S126, the HMI control unit 222 determines whether or not an instruction to execute the analysis algorithm has been issued.

[0114] For example, the user determines whether or not to adopt the proposed analysis algorithm. If the user determines to adopt the proposed analysis algorithm, the user selects the analysis algorithm to adopt when multiple analysis algorithms are presented. The user inputs, via the input unit 201, whether or not to adopt the proposed analysis algorithm or the result of the analysis algorithm selection to the information processing unit 113.

[0115] If the HMI control unit 222 determines, based on the user's input, that execution of the analysis algorithm has not been instructed, the process returns to step S121.

[0116] Thereafter, steps S121 to S126 are repeatedly executed until it is determined in step S124 that an analysis algorithm has been specified, or until it is determined in step S126 that execution of an analysis algorithm has been instructed, thereby presenting the user with alternative candidates for reference documents and analysis algorithms while changing the analysis conditions as necessary.

[0117] On the other hand, if it is determined in step S126 that execution of the analysis algorithm has been instructed, the process proceeds to step S127.

[0118] Also, in step S124, if the analysis conditions entered by the user include an analysis algorithm, the algorithm setting unit 241 determines that an analysis algorithm has been specified, and the processing of steps S125 to S126 is skipped, and the processing proceeds to step S127.

[0119] In step S127, the parameter setting unit 242 sets analysis parameters. For example, the parameter setting unit 242 obtains information on analysis parameters used in reference documents for the analysis algorithm to be executed from the literature DB 206. The parameter setting unit 242 sets the analysis parameters as parameters to be used in executing the analysis algorithm.

[0120] For example, if analysis parameters are not registered for a reference document in the document DB 206, the user may set the analysis parameters, or the analysis parameters may be set to standard values ​​in the analysis algorithm being implemented.

[0121] In step S128, the analysis editing unit 221 analyzes the experimental data using the set analysis algorithm and analysis parameters. Specifically, the algorithm setting unit 241 supplies algorithm information related to the analysis algorithm to the analysis unit 233. The parameter setting unit 242 supplies parameter information related to the analysis parameters to the analysis unit 233. The analysis unit 233 analyzes the experimental data stored in the experiment data storage unit 205 using the set analysis algorithm and analysis parameters.

[0122] For example, when the document with ID2 in the document DB 206 in FIG. 4 is selected as a reference document, the analysis parameters are set to n_neighbors=20 and n_comp=2, and UMAP is implemented as the analysis algorithm.

[0123] In step S129, the information processing unit 113 presents the analysis results. Specifically, the analysis unit 233 supplies analysis information indicating the analysis results of the experimental data to the HMI control unit 222. The output unit 203, under the control of the HMI control unit 222, presents the analysis results of the experimental data based on the analysis information.

[0124] FIG. 8 shows an example of the presentation of the analysis results of the experimental data.

[0125] For example, as shown in FIG. 8A, it is presented that clustering and dimensionality reduction of experimental data was performed.

[0126] For example, as shown in B of Fig. 8, a distribution map of cell data (particle data) showing the results of dimensionality reduction of experimental data is presented. For example, each cell data is compressed into two dimensions of dimensions 1 and 2, and the distribution of each cell data in the two-dimensional space of dimensions 1 and 2 is presented.

[0127] For example, as shown in Fig. 8C, a table showing the clustering results is presented. For example, the values ​​of dimension 1 and dimension 2 of each cell data and the cluster number of the cluster to which each cell data belongs are presented.

[0128] Then, the analysis process ends.

[0129] Returning to FIG. 6, in step S102, the information processing unit 113 executes additional analysis processing.

[0130] Here, the additional analysis process will be described in detail with reference to the flowchart of FIG.

[0131] In step S141, the HMI control unit 222 determines whether or not an instruction to correct the analysis result has been issued.

[0132] For example, under the control of the HMI control unit 222, the output unit 203 presents the analysis results of the experimental data, and if corrections to the analysis results (additional analysis) are necessary, prompts the user to input correction instructions in natural language.

[0133] In response to this, for example, the user looks at the analysis results of the experimental data presented by the output unit 203 and determines whether or not the analysis results need to be revised. If the user determines that the analysis results need to be revised, the user instructs the information processing unit 113 to revise the analysis results via the input unit 201. On the other hand, if the user determines that additional analysis is not necessary, the user instructs the information processing unit 113 via the input unit 201 to end the analysis.

[0134] If the HMI control unit 222 determines that an instruction to correct the analysis results has been issued based on the instruction entered by the user, the process proceeds to step S142.

[0135] In step S142, the control unit 202 sets the conditions for correcting the analysis results. Specifically, the analysis method setting unit 232 sets the conditions for correcting the analysis results based on the instructions for correcting the analysis results. For example, the analysis method setting unit 232 sets a performance index for determining the quality of the analysis results, and sets the correction conditions so that the performance index becomes the highest.

[0136] Here, a specific method for setting the correction conditions will be described with reference to the sequence diagram of Fig. 10. It is assumed below that the distribution diagram of cell data in Fig. 8B is presented to the user.

[0137] In step S161, for example, the user inputs an instruction to the information processing unit 113 via the input unit 201, such as "Move the group on the upper right further apart."

[0138] In response to this, in step S162, the HMI control unit 222 recognizes the user's instruction using the LLM 207. Then, the output unit 203, under the control of the HMI control unit 222, presents the recognized instruction to the user. For example, it is presented that the instruction has been recognized as being to move the shaded portion (cell population 301) away from the other portion (cell population 302) in the distribution diagram of the cell data. At this time, for example, the display mode of the cell population 301 changes, emphasizing that the "upper right group" in the user's instruction has been recognized as the cell population 301.

[0139] In response to this, in step S163, the user inputs the answer "yes" to the information processing unit 113 via the input unit 201.

[0140] In response to this, the HMI control unit 222 recognizes that it has correctly recognized the contents of the user's instruction, and notifies the analyzing and editing unit 221 of the contents of the user's instruction.

[0141] In response to this, the analysis method setting unit 232 sets the distance between the median values ​​of the X and Y coordinates of cell population 301 and the median values ​​of the X and Y coordinates of cell population 302 (hereinafter referred to as the inter-population distance) as a performance index. Then, the analysis method setting unit 232 sets maximizing the inter-population distance as a modification condition.

[0142] In step S143, the analysis and editing unit 221 searches for analysis parameters that satisfy the modification conditions.

[0143] For example, the parameter setting unit 242 changes the analysis parameters and supplies parameter information indicating the changed analysis parameters to the analysis unit 233. The analysis unit 233 analyzes the experimental data using the changed analysis parameters and supplies analysis information indicating the analysis results to the analysis method setting unit 232. For example, this process is performed while comprehensively changing the analysis parameters.

[0144] For example, when UMAP is implemented as the analysis algorithm, dimensionality reduction by UMAP is performed while n_neighbors is incremented by 1 from 1 to 100. Then, n_neighbors that maximizes the inter-group distance is searched for.

[0145] In step S144, the information processing unit 113 presents the corrected analysis results. Specifically, the analysis unit 233 supplies analysis information indicating the analysis results that satisfied the correction conditions in the processing of step S143 (for example, when the performance index became the highest) to the HMI control unit 222. Under the control of the HMI control unit 222, the output unit 203 presents the analysis results of the experimental data based on the analysis information.

[0146] For example, in step S164 of FIG. 10, the output unit 203, under the control of the HMI control unit 222, presents a distribution diagram of cell data in which the inter-population distance between the cell population 301 and the cell population 302 is maximum.

[0147] Thereafter, the process returns to step S141, and steps S141 to S144 are repeatedly executed until it is determined in step S141 that an additional analysis has not been instructed. That is, the process of interactively adjusting the analysis parameters according to the user's instructions, executing the analysis algorithm using the adjusted analysis parameters, and presenting the analysis results is repeatedly executed. This allows the user to obtain analysis results that are closer to the results they desire.

[0148] On the other hand, if it is determined in step S141 that no instruction to correct the analysis results has been given, the additional analysis process ends.

[0149] If it is determined in the initial process of step S141 that no instruction has been given to correct the analysis results, the additional analysis process ends without performing additional analysis.

[0150] Returning to FIG. 6, in step S103, the information processing unit 113 executes an editing process.

[0151] The editing process will now be described in detail with reference to the flowchart of FIG.

[0152] In step S201, the information processing unit 113 receives difference information from the reference document. For example, under the control of the HMI control unit 222, the output unit 203 presents a comparison result between the reference document and the analysis result of the current experimental data, and prompts the user to input differences from the reference document (e.g., new findings) in natural language.

[0153] In response to this, for example, the user compares the analysis results of the current experimental data with the analysis results of the reference document. If the user determines that the analysis results of the current experimental data include differences from the analysis results of the reference document, the user inputs difference information indicating the differences from the reference document to the information processing unit 113 via the input unit 201. On the other hand, if the user determines that the analysis results of the current experimental data do not include differences from the analysis results of the reference document, the user inputs information indicating that there are no differences from the reference document to the information processing unit 113 via the input unit 201.

[0154] For example, FIG. 12 shows an example of an HMI for this process.

[0155] For example, in step S221, a distribution map of cell data from the analysis results of the reference literature (left side) and a distribution map of cell data from the analysis results of the current experimental data (right side) are presented side by side, and the differences between the two are presented. The user is also asked whether the analysis results of the current experimental data have revealed any findings in relation to the analysis results of the reference literature. This prompts the user to input, in natural language, information about the differences between the analysis results of the reference literature and the current experimental data.

[0156] In response to this, in step S222, the user replies via the input unit 201 that it has been found that the proportion of XX cells in the comparison group (the analysis results of the reference literature) is lower than that in the control group (the analysis results of the current experimental data).

[0157] In step S202, the HMI control unit 222 determines whether difference information from the reference document has been input. For example, the HMI control unit 222 recognizes the content of the user's response using the LLM 207. If the HMI control unit 222 determines based on the recognition result that difference information from the reference document has been input, the process proceeds to step S203.

[0158] In step S203, the information processing unit 113 creates an experiment report based on the reference documents, analysis results, and difference information. Specifically, the HMI control unit 222 supplies the difference information input by the user to the analysis and editing unit 221. The analysis unit 233 supplies the analysis information to the editing unit 234. The editing unit 234 acquires the text of the reference documents from the literature DB 206. The editing unit 234 inputs the reference documents (the texts), analysis information, and difference information into the LLM 207 and acquires the text output from the LLM 207. For example, the editing unit 234 creates an experiment report in which the text acquired from the LLM 207 is written in the same format as the reference documents.

[0159] This will create an experiment report that includes the analysis results of the experiment and any differences from the reference literature.

[0160] Thereafter, the process proceeds to step S205.

[0161] On the other hand, if the HMI control unit 222 determines in step S202 that difference information from the reference document has not been input, the process proceeds to step S204.

[0162] In step S204, the information processing unit 113 creates an experiment report based on the reference documents and the analysis results. Specifically, the HMI control unit 222 notifies the analysis and editing unit 221 that no difference information has been input by the user. The analysis unit 233 supplies the analysis information to the editing unit 234. The editing unit 234 acquires the text of the reference documents from the literature DB 206. The editing unit 234 inputs the reference documents (the texts) and the analysis information into the LLM 207 and acquires the text output from the LLM 207. For example, the editing unit 234 creates an experiment report in which the text acquired from the LLM 207 is written in the same format as the reference documents.

[0163] This will create an experiment report that includes the analysis results of this experiment.

[0164] Thereafter, the process proceeds to step S205.

[0165] In step S205, the information processing unit 113 presents the experiment report. Specifically, the editing unit 234 supplies the created experiment report to the HMI control unit 222. The output unit 203 presents the experiment report under the control of the HMI control unit 222.

[0166] The editing process then ends.

[0167] For example, the editing unit 234 may further revise the experiment report in accordance with instructions from the user.

[0168] <Literature Information Curation Processing> Next, the literature information curation processing executed by the information processing unit 113 will be described with reference to the flowchart of FIG.

[0169] In step S301, the curation unit 223 determines whether or not to perform curation of the document information. This process is repeatedly executed until it is determined that the document information should be curated.

[0170] On the other hand, if it is determined in step S301 that the document information is to be curated, the process proceeds to step S302. Note that the document information is curated, for example, periodically or when instructed by the user.

[0171] In step S302, the curation unit 223 searches for new and updated documents. For example, the curation unit 223 searches for new documents newly published on the Internet or documents updated since the previous curation via the communication unit 204. For example, the curation unit 223 searches public paper databases such as PubMed (trademark) and bioRxiv. Then, the curation unit 223 acquires the new and updated documents.

[0172] In step S303, the curation unit 223 analyzes the new and updated documents. For example, the curation unit 223 uses the LLM 207 to analyze the documents acquired in the process of step S302.

[0173] This allows obtaining information on the analysis algorithms, analysis parameters, experimental conditions (including experimental equipment) of new and updated documents.

[0174] In step S304, the curation unit 223 registers information about the new document and the updated document. Specifically, based on the analysis results, the curation unit 223 registers information about the new document and the updated document in the document DB 206. For example, the URLs, texts, analysis algorithms, experimental conditions (including experimental equipment), etc. of the new document and the updated document are registered in the document DB 206.

[0175] Thereafter, the process returns to step S301, and the processes from step S301 onwards are executed.

[0176] In this way, experimental data can be analyzed easily and in a short time. For example, regardless of the user's level of knowledge, the experimental data can be analyzed using appropriate analysis algorithms and analysis parameters without repeated trial and error. Furthermore, the user can adjust the analysis results of the experimental data using natural language, without using technical terms, etc.

[0177] Furthermore, an experiment report can be created easily and quickly. That is, an experiment report including the analysis results of the experimental data is automatically created based on the reference literature, without the user having to obtain new knowledge from the analysis results and write it down.

[0178] <<2. Modifications>> Modifications of the above-described embodiments of the present technology will now be described.

[0179] <Modifications for Correcting Analysis Results> In the above explanation, an example was given in which analysis parameters were changed when correcting the analysis results of experimental data, but the analysis algorithm may also be changed.

[0180] For example, suppose that the result shown in Figure 8B has been obtained by dimensionality reduction of experimental data, and the user inputs an instruction such as "Perform clustering that best represents the group in the upper right corner (cell group 301)."

[0181] In this case, the modified conditions are set so that the cell population 301 can be represented by one cluster as accurately as possible, and clustering is performed. For example, optimal clustering is achieved when cells contained in the cell population 301 belong to the same cluster and other cells do not belong to that cluster. For example, the F value is set as the performance index, and clustering is performed under modified conditions that maximize the F value.

[0182] For example, FlowSOM and K-means are used as analytical algorithms (clustering algorithms).

[0183] For example, when the analysis algorithm is FlowSOM, the number of times of learning, the number of divisions, etc. are used as analysis parameters. Then, the number of times of learning, the number of divisions, etc. are adjusted so that the F-measure is maximized.

[0184] For example, when the analysis algorithm is K-means, the number of divisions is used as an analysis parameter, and the number of divisions is adjusted so that the F-measure is maximized.

[0185] For example, it is also possible to expand the results of dimensionality reduction into a conventional two-dimensional plot, or to expand the results of clustering into a conventional two-dimensional plot.

[0186] <Modifications Regarding Allocation of Processing> For example, part of the processing of the information processing unit 113 described above may be executed by the server 12 .

[0187] For example, the experiment data storage unit 205, the literature DB 206, and the LLM 207 may be provided in the server 12. For example, the server 12 may be configured to perform curation of the literature DB 206.

[0188] <Application Examples of the Present Technology> The present technology may be applied to the analysis of particles other than biological particles. For example, beads may be analyzed for calibration purposes. For example, the particles to be analyzed may be industrially synthesized particles such as latex particles, gel particles, or industrial particles. For example, the industrially synthesized particles may be particles synthesized from organic resin materials such as polystyrene and polymethyl methacrylate, inorganic materials such as glass, silica, and magnetic materials, or metals such as gold colloid and aluminum. Each particle may be spherical or non-spherical, and there are no particular limitations on its size or mass.

[0189] <<3. Others>> <Example of Computer Configuration> The above-described series of processes can be executed by hardware or software. When the series of processes is executed by software, the programs that make up the software are installed on a computer. Here, the computer includes a computer built into dedicated hardware, and a general-purpose personal computer, for example, that can execute various functions by installing various programs.

[0190] FIG. 14 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processes by a program.

[0191] In the computer 1000 , a CPU (Central Processing Unit) 1001 , a ROM (Read Only Memory) 1002 , and a RAM (Random Access Memory) 1003 are interconnected by a bus 1004 .

[0192] An input / output interface 1005 is further connected to the bus 1004. An input unit 1006, an output unit 1007, a storage unit 1008, a communication unit 1009, and a drive 1010 are connected to the input / output interface 1005.

[0193] The input unit 1006 includes input switches, buttons, a microphone, an image sensor, etc. The output unit 1007 includes a display, a speaker, etc. The storage unit 1008 includes a hard disk, a non-volatile memory, etc. The communication unit 1009 includes a network interface, etc. The drive 1010 drives removable media 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory.

[0194] In the computer 1000 configured as described above, the CPU 1001 performs the above-described series of processes by, for example, loading a program recorded in the memory unit 1008 into the RAM 1003 via the input / output interface 1005 and the bus 1004 and executing it.

[0195] The program executed by the computer 1000 (CPU 1001) can be provided by being recorded on a removable medium 1011 such as a package medium, for example. The program can also be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

[0196] In the computer 1000, the program can be installed in the storage unit 1008 via the input / output interface 1005 by inserting the removable medium 1011 into the drive 1010. The program can also be received by the communication unit 1009 via a wired or wireless transmission medium and installed in the storage unit 1008. Alternatively, the program can be installed in the ROM 1002 or the storage unit 1008 in advance.

[0197] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0198] In this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all of the components are housed in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0199] Furthermore, the embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present technology.

[0200] For example, the present technology can be configured as a cloud computing system in which a single function is shared and processed collaboratively by a plurality of devices via a network.

[0201] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by a plurality of devices.

[0202] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0203] <Examples of Combinations of Configurations> The present technology can also have the following configurations.

[0204] (1) An information processing method including an information processing device setting, based on a reference document, at least one of an analysis algorithm or analysis parameters used to analyze experimental data including a plurality of particle data based on light from each of a plurality of particles, and analyzing the experimental data using the analysis algorithm and the analysis parameters. (2) The information processing method described in (1), further including, based on experimental conditions for obtaining the experimental data, the information processing device identifying the reference document. (3) The information processing method described in (2), further including, based on experimental conditions for obtaining the experimental data, the information processing device identifying the reference document related to an experiment similar to the experimental conditions. (4) The information processing method described in (3), further including, based on the experimental conditions, the type of cell that is the particle, and a combination of an antigen and a labeling substance to be analyzed. (5) The information processing method described in (4), further including, based on the experimental conditions, information related to equipment used in the experiment. (6) The information processing method according to any one of (1) to (5), further including the information processing device outputting the analysis results of the experimental data, and analyzing the experimental data by changing at least one of the analysis algorithm or the analysis parameters based on an instruction to modify the analysis results. (7) The information processing method according to (6), further including the information processing device setting a modification condition for the analysis results based on the instruction to modify, and modifying at least one of the analysis algorithm or the analysis parameters so as to satisfy the modification condition. (8) The information processing method according to (6) or (7), further including the instruction to modify is input in natural language. (9) The information processing method according to any one of (1) to (8), further including the information processing device outputting an experiment report including the analysis results of the experimental data based on the reference literature. (10) The information processing method according to (9), further including the information processing device presenting a comparison result between the reference literature and the analysis results. (11) The information processing method according to (9) or (10), wherein the information processing device further creates the experiment report based on difference information between the reference document and the analysis result.(12) The information processing method according to (11), wherein the information processing device presents a difference between the reference document and the analysis result and prompts a user to input the difference information. (13) The information processing method according to (11) or (12), wherein the information processing device further prompts a user to input the difference information in natural language. (14) The information processing method according to any of (11) to (13), wherein the information processing device generates the experiment report using LLM (Large Language Models). (15) An information processing device comprising: an analysis method setting unit that sets at least one of an analysis algorithm or analysis parameters used for analyzing experimental data including a plurality of particle data based on light from each of a plurality of particles, based on a reference document; and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameters. (16) An information processing system comprising: a detection unit that detects light from each of a plurality of particles; and an information processing unit, wherein the information processing unit comprises: an analysis method setting unit that sets, based on a reference document, at least one of an analysis algorithm or an analysis parameter used to analyze experimental data including a plurality of particle data based on light from each of the plurality of particles; and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameter.

[0205] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0206] 1 Information processing system, 11-1 to 11-n Biological sample analyzer, 12-1, 12-2 Server, 111 Light irradiation unit, 112 Detection unit, 113 Information processing unit, 114 Fractionation unit, 202 Control unit, 203 Output unit, 206 Literature DB, 207 LLM, 221 Analysis editing unit, 222 HMI control unit, 223 Curation unit, 231 Reference literature setting unit, 232 Analysis method setting unit, 233 Analysis unit, 234 Editing unit, 241 Algorithm setting unit, 242 Parameter setting unit

Claims

1. An information processing method comprising: an information processing device setting, based on a reference document, at least one of an analysis algorithm or analysis parameters used to analyze experimental data including a plurality of particle data based on light from each of a plurality of particles; and analyzing the experimental data using the analysis algorithm and the analysis parameters.

2. The information processing method according to claim 1, further comprising: said information processing device identifying said reference literature based on experimental conditions for obtaining said experimental data.

3. The information processing method according to claim 2, wherein the information processing device identifies the reference literature relating to an experiment similar to the experimental conditions.

4. The information processing method according to claim 3, wherein the experimental conditions include the type of cells that are the particles, and a combination of antigens and labeling substances to be analyzed.

5. The information processing method according to claim 4, wherein the experimental conditions further include information about the equipment used in the experiment.

6. The information processing method according to claim 1, further comprising: outputting the analysis results of the experimental data; and analyzing the experimental data by changing at least one of the analysis algorithm or the analysis parameters based on instructions for modifying the analysis results.

7. The information processing method according to claim 6, wherein the information processing device sets a modification condition for the analysis result based on the modification instruction content, and changes at least one of the analysis algorithm or the analysis parameters so as to satisfy the modification condition.

8. The information processing method according to claim 6, further comprising: inputting the instruction for correction in a natural language.

9. The information processing method according to claim 1, further comprising the step of: outputting an experiment report including an analysis result of the experiment data based on the reference literature.

10. The information processing method according to claim 9, further comprising the information processing device presenting a comparison result between the reference document and the analysis result.

11. The information processing method according to claim 9, wherein the information processing device further creates the experiment report based on difference information between the reference literature and the analysis results.

12. The information processing method according to claim 11, wherein the information processing device presents the differences between the reference document and the analysis result to prompt the user to input the difference information.

13. The information processing method according to claim 11, further comprising: prompting a user to input the difference information in natural language.

14. The information processing method according to claim 11, wherein the information processing device generates the experiment report using LLM (Large Language Models).

15. An information processing device comprising: an analysis method setting unit that sets at least one of an analysis algorithm or analysis parameters used to analyze experimental data including multiple particle data based on light from each of multiple particles, based on reference literature; and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameters.

16. An information processing system comprising: a detection unit that detects light from each of a plurality of particles; and an information processing unit, wherein the information processing unit comprises: an analysis method setting unit that sets, based on reference literature, at least one of an analysis algorithm or analysis parameters used to analyze experimental data including a plurality of particle data based on light from each of the plurality of particles; and an analysis unit that analyzes the experimental data using the analysis algorithm and the analysis parameters.

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