Information processing system and server system

Abstract

The purpose of the present invention is to provide technology with which it is possible to flexibly and seamlessly use a resource that performs data analysis processing, irrespective of the type of a network, such as a public cloud network or an on-premise network.　The present disclosure provides an information processing system including a management system which manages: a program for analysing at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light; and an analysis server for performing at least one of deployment and execution of the program.

Description

Information processing system and server system

[0001] The present disclosure relates to an information processing system and a server system, and more particularly to an information processing system and a server system that analyze at least one of light intensity data and fluorescent label intensity data obtained by irradiating a biological sample with light.

[0002] For example, particle characteristics are measured by labeling a particle population, such as cells, microorganisms, and liposomes, with a fluorescent dye, irradiating each particle in the particle population with a laser beam, and measuring the intensity and / or pattern of fluorescence emitted from the excited fluorescent dye. A flow cytometer is a typical example of a particle analyzer that performs such measurements.

[0003] As a technology relating to the processing of data acquired by a flow cytometer, in particular light intensity data, for example, Patent Document 1 listed below discloses "a server system including an automatic analysis processing unit that generates output data by performing an analysis process on light intensity data or fluorescent label intensity data acquired by irradiating a biological sample with light, an analysis result data storage unit that stores the output data generated based on the light intensity data or the fluorescent label intensity data, and an interactive analysis processing unit that analyzes the fluorescent label intensity data based on an analysis command for the output data output to an output device and outputs analysis result data."

[0004] International Publication No. 2022 / 080102

[0005] Cloud services such as SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service) can be used to process data acquired by a flow cytometer. Cloud services charge only for what is used, which reduces costs compared to providing your own servers and software. In particular, data analysis using this technology requires a large amount of computational processing, which means the initial and running costs of the servers and software are a significant burden. Using cloud services can significantly reduce these costs.

[0006] On the other hand, because data acquired by flow cytometers may contain personal or confidential information, there is a need to store this data in an on-premise environment rather than in a cloud environment. However, as mentioned above, data analysis using this technology requires a large amount of computational processing, which means that the initial and running costs of the server and software are a significant burden.

[0007] For this reason, it is preferable to build a system that maximizes the benefits of both cloud and on-premise environments.

[0008] Therefore, a primary object of the present disclosure is to provide a technology that enables flexible and seamless use of resources for performing data analysis processing, regardless of the type of network, such as a public cloud network, an on-premise network, etc. Note that the object of the present disclosure is not limited thereto, and may be, for example, to solve one or more of the problems described below in this specification.

[0009] The present disclosure provides an information processing system including a management system that manages a program for analyzing at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light, and an analysis server that deploys and / or executes the program. The management system may include: a resource management unit that manages resource information related to computing resources of the analysis server; a program management unit that manages program information related to the program; and a connection unit that connects to at least one of a system and a device different from the management system. The information processing system may further include an agent unit that connects to the analysis server and the connection unit. The management system may connect to a first information and communication network, and the agent unit may connect to a second information and communication network, and the first information and communication network and the second information and communication network may be connected to each other via a communication processing unit. The first information and communication network may be a public cloud network, and the second information and communication network may be a private cloud network or an on-premises network. The agent unit may communicate with the connection unit by long polling. The agent unit may include a resource registration unit that transmits resource information of the analysis server to the resource management unit. The agent unit may include a system construction unit that deploys and / or executes the program on the analysis server.The information processing system may further include a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein the data analysis client terminal transmits analysis information related to an analysis process of at least one of the light intensity data and the fluorescent label intensity data to the connection unit, wherein the connection unit determines the program that will perform the analysis process and the analysis server that will at least one of deploy and execute the program based on at least one of the analysis information, the resource information, and the program information, and transmits information about the determined analysis server and the program to the system construction unit, wherein the system construction unit at least one of deploys and executes the program on the analysis server based on the received information about the analysis server and the program, and wherein the connection unit determines the program that will perform the analysis process and the analysis server that will at least one of deploy and execute the program based on at least one of the analysis information, the resource information, the program information, and information related to a usage fee for the analysis server, and transmits information about the determined analysis server and the program to the system construction unit. The information processing system may further include a data dividing unit that divides at least one of the light intensity data and the fluorescent label intensity data based on the resource information and transmits each of the divided data to different analysis servers. The information processing system may further include a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, and the connection unit may transmit information about the analysis server that deploys and / or executes the program to the data analysis client terminal. The data analysis client terminal may accept designation of at least one of the analysis server and the program, and transmit information about at least one of the analysis server and the program to the connection unit.The present disclosure also provides a server system including a system construction unit that deploys and / or executes, on an analysis server, a program for analyzing at least one of light intensity data and fluorescent label intensity data obtained by irradiating a biological sample with light, wherein at least one of the program and the analysis server is determined based on a database that stores information regarding at least one of the program and the analysis server. According to the present disclosure, resources for data analysis processing can be flexibly and seamlessly used regardless of the type of network, such as a public cloud network or an on-premises network. Note that the effects described herein are not necessarily limited to those described herein and may be any of the effects described herein.

[0010] 1 is a schematic diagram of a configuration of a flow cytometer. FIG. 1 is a diagram illustrating an example of an experimental flow when the present technology is applied to flow cytometry. FIG. 2 is a diagram illustrating an example of gate setting. FIG. 3 is a diagram for explaining surface markers. FIG. 4 is a block diagram illustrating an example of a configuration of an information processing system 100 according to an embodiment of the present technology. FIG. 5 is an example of a database managed by a resource management unit 71 according to an embodiment of the present technology. FIG. 6 is an example of a database managed by a program management unit 72 according to an embodiment of the present technology. FIG. 7 is a flowchart illustrating an example of a processing flow of the information processing system 100 according to an embodiment of the present technology. FIG. 8 is a schematic diagram illustrating an example of a processing flow of long polling. FIG. 9 is a block diagram illustrating an example of a configuration of an analysis server 101 according to an embodiment of the present technology. FIG. 10 is a block diagram illustrating an example of a configuration of a data analysis client terminal 20 according to an embodiment of the present technology. FIG. 11 is a block diagram illustrating an example of a configuration of a data analysis client terminal 20 according to an embodiment of the present technology. FIG. 12 is a diagram illustrating an example of a window that the data analysis client terminal 20 according to an embodiment of the present technology causes an output device to output. FIG. 13 is a block diagram illustrating an example of a configuration of a data acquisition client terminal 30 according to an embodiment of the present technology. FIG. 14 is a schematic diagram illustrating an example of a configuration of a biological sample analyzer 40 according to an embodiment of the present technology. FIG. 15 is a block diagram illustrating an example of a configuration of an information processing system 100 according to an embodiment of the present technology. FIG. 16 is a flowchart illustrating an example of a processing flow of the information processing system 100 according to an embodiment of the present technology. Fig. 1 is a diagram showing an example of a window that a data analysis client terminal 20 according to an embodiment of the present technology causes an output device to output; Fig. 2 is a block diagram showing an example of a configuration of an information processing system 100 according to an embodiment of the present technology; Fig. 3 is a flowchart showing an example of a processing flow of the information processing system 100 according to an embodiment of the present technology; Fig. 4 is a block diagram showing an example of a configuration of the information processing system 100 according to an embodiment of the present technology; Fig. 5 is a flowchart showing an example of a processing flow of the information processing system 100 according to an embodiment of the present technology;

[0011] Preferred embodiments for implementing the present disclosure will be described below. Note that the embodiments described below are representative embodiments of the present disclosure, and the scope of the present disclosure is not limited to these embodiments. Note that the present disclosure will be described in the following order. 1. First Embodiment of the Present Technology (Example 1 of Information Processing System) (1) Description of Related Technology (2) Overview of Information Processing System (3) Management System (3-1) Resource Management Unit (3-2) Program Management Unit (3-3) Connection Unit (4) Server System (4-1) Agent Unit (4-2) Client-Server Communication (4-3) Analysis Server (5) Data Analysis Client Terminal (6) Data Acquisition Client Terminal (7) Biological Sample Analyzer (7-1) Biological Sample (7-2) Flow Channel (7-3) Light Irradiation Unit (7-4) Detection Unit (7-5) Information Processing Unit (7-6) Fractionation Unit 2. Second Embodiment of the Present Technology (Example 2 of Information Processing System) 3. Third Embodiment of the Present Technology (Example 3 of Information Processing System) 4. 4. Fourth embodiment of the present technology (example 4 of information processing system) 5. Fifth embodiment of the present technology (example 5 of information processing system) 6. Sixth embodiment of the present technology (example 6 of information processing system) 7. Seventh embodiment of the present technology (example of server system)

[0012] [1. First Embodiment of the Present Technology (Example 1 of Information Processing System)] [(1) Description of Related Art] Flow cytometers can be broadly classified into filter-type and spectral-type flow cytometers, for example, from the perspective of the optical system for fluorescence measurement. A filter-type flow cytometer can employ a configuration such as that shown in FIG. 1-1 to extract only the desired optical information from the desired fluorescent dye. Specifically, light generated by irradiating particles with light is split into multiple beams using a wavelength separation means DM, such as a dichroic mirror, and passed through different filters. Each of the split beams is then measured using multiple detectors, such as photomultiplier tubes (PMTs). That is, a filter-type flow cytometer detects multicolor fluorescence by detecting fluorescence in each wavelength band corresponding to each fluorescent dye using a detector corresponding to each fluorescent dye. In this case, when multiple fluorescent dyes with closely spaced fluorescence wavelengths are used, a fluorescence correction process can be performed to calculate the fluorescence intensity more accurately.

[0013] On the other hand, spectral flow cytometers analyze the fluorescence intensity of each particle by deconvoluting (unmixing) the fluorescence data obtained by detecting light emitted from particles irradiated with light using spectral information from the fluorescent dyes used for staining. As shown in FIG. 1-2, spectral flow cytometers use a prism spectroscopic optical element P to disperse fluorescence. Furthermore, to detect the dispersed fluorescence, spectral flow cytometers are equipped with an array detector (e.g., an array photomultiplier tube PMT) instead of the multiple photodetectors found in filter flow cytometers. Compared to filter flow cytometers, spectral flow cytometers are more easily affected by fluorescence leakage and are therefore more suitable for analysis using multiple fluorescent dyes.

[0014] In recent years, multicolor analysis using multiple fluorescent dyes has become common in flow cytometry to facilitate comprehensive interpretation in both basic medicine and clinical fields. The number of fluorescent dyes used in a single multicolor analysis is on the rise. When multiple fluorescent dyes are used in a single measurement, as described above, fluorescence from fluorescent dyes other than the target fluorescent dye leaks into each detector in a filter-type flow cytometer, reducing analytical accuracy. When using a large number of colors, the problem of fluorescent leakage can be solved by using a spectral flow cytometer.

[0015] An example of an experimental flow using a flow cytometer will be described below with reference to FIG.

[0016] The flow of an experiment using a flow cytometer can be broadly divided into the following steps: experimental planning (Figure 2, "1: Plan"), which considers the cells to be tested and the method for detecting them, and prepares fluorescently labeled antibody reagents; sample preparation (Figure 2, "2: Preparation"), which actually stains and prepares the cells to a state suitable for measurement; FCM measurement (Figure 2, "3: FCM"), which measures the fluorescence intensity of each stained cell using a flow cytometer; and data analysis (Figure 2, "4: Data Analysis"), which performs various data processing operations to obtain the desired analytical results from the data recorded in the FCM measurement. These steps can be repeated as necessary.

[0017] In the experimental planning step, first, it is determined which molecules (e.g., antigens or cytokines) will be used to determine the expression of microparticles (mainly cells) that are to be detected using a flow cytometer. In other words, it is determined which markers will be used to detect the microparticles. This determination can be made based on information such as past experimental results and papers. Next, it is considered which fluorescent dyes will be used to detect the markers. For example, it is determined by comprehensively determining information such as the number of markers to be detected simultaneously, the specifications of the available FCM equipment, available fluorescently labeled reagents, the spectrum and brightness of the fluorescent dyes, price, and delivery time, and then determining the combination of fluorescently labeled antibody reagents required for the actual experiment. This process of determining the reagent combination is generally called panel design in FCM.

[0018] In the sample preparation process, the experimental subject is first processed to a state suitable for FCM measurement. For example, cell separation and purification may be performed. For example, blood-derived immune cells are extracted by hemolysis and density gradient centrifugation to remove red blood cells and extract white blood cells. The extracted target cell population is then stained using fluorescently labeled antibodies.

[0019] In the FCM measurement process, when optically analyzing microparticles, first, excitation light is emitted from the light source of the light irradiation unit of the flow cytometer and irradiated onto the microparticles flowing in the flow channel. Next, the fluorescence emitted from the microparticles is detected by the detection unit of the flow cytometer. Specifically, a dichroic mirror or bandpass filter is used to separate only light of a specific wavelength (target fluorescence) from the light emitted from the microparticles, and this is detected by a detector such as a PMT. At this time, the fluorescence is separated using, for example, a prism or diffraction grating, and light of different wavelengths is detected in each channel using a detector such as a 32-channel PMT. This makes it easy to obtain spectral information of the detected light (fluorescence).

[0020] A flow cytometer may have a function for recording the fluorescence information of each microparticle acquired by FCM measurement together with scattered light information, time information, and position information other than the fluorescence information. This recording function may be mainly performed by the memory or disk of a computer. In typical cell analysis, thousands to millions of microparticles are analyzed under a single experimental condition, so a large amount of information must be recorded in an organized manner for each experimental condition.

[0021] In the data analysis step, a computer or the like is used to quantify the light intensity data in each wavelength region detected in the FCM measurement step, and the fluorescence amount (intensity) for each fluorescent dye used is determined. This analysis uses a correction method using a standard calculated from experimental data. The standard is calculated by statistical processing using two types of standard: measurement data for microparticles stained with only one fluorescent dye and measurement data for unstained microparticles. The calculated fluorescence amount can be recorded in a data recording unit installed in the computer, along with information such as the name of the fluorescent molecule, the date of measurement, and the type of microparticle. The fluorescence amount (fluorescence spectrum data) of the sample estimated in the data analysis is saved and displayed in a graph depending on the purpose, and the fluorescence amount distribution of the microparticles can be analyzed.

[0022] For example, gates are often set to analyze the fluorescence intensity distribution, allowing the proportion of target cells in a sample to be calculated. For example, as shown in FIG. 3 , by generating a two-dimensional plot of forward scatter (FSC) and side scatter (SSC) and selecting a specific range within the plot, the proportion of monocytes and lymphocytes among the blood cells contained in PBMCs can be determined. Furthermore, by setting a gate and expanding the data for lymphocytes expressing specific surface markers, the proportion of B cells, T cells, and NK cells among lymphocytes can be calculated. Furthermore, the proportion of memory B cells among B cells, the proportion of killer T cells and helper T cells among T cells, and the proportion of naive T cells and memory T cells can also be determined. It is known that the surface markers expressed by each type of cell vary depending on the cell type, as shown in FIG. 4 . Therefore, cells in a sample can be examined by appropriately selecting antibodies that bind to surface markers and fluorescent dyes that label each antibody, and then analyzing the sample using a flow cytometer.

[0023] The information processing system according to the present disclosure and the components included in the system can be used for the analysis in the data analysis step.

[0024] [(2) Overview of Information Processing System] In recent years, with the advancement of technology in the fields of computers and reagents, the number of parameters that can be measured at one time by a flow cytometer has increased dramatically. As a result, against the backdrop of an increase in the amount of measured data and the increase in the computational resources required for analysis, there is a growing trend to use cloud platforms provided by cloud vendors to store data in a cloud environment and perform analysis in a cloud environment.

[0025] When using cloud services such as cloud platforms and SaaS, there is no need to install and configure high-spec servers or workstations for analysis, which was previously required when performing analysis in an on-premise environment. This has the advantage of eliminating the time and financial costs involved in operations, such as dealing with hardware failures and aging, and dealing with storage depletion.

[0026] On the other hand, because the measurement data obtained by flow cytometers is highly confidential, there are a certain number of companies, research institutions, and users who, mainly for security reasons, do not want to use a cloud environment to store and analyze measurement data, but rather want to do so in an on-premises environment.

[0027] As such, there are needs for both cloud and on-premise environments. Therefore, it is desirable to realize a system that can support a hybrid configuration that combines cloud and on-premise environments, and that can flexibly configure an analysis execution environment to suit the needs of the user and execute analysis.

[0028] Therefore, the present technology provides an information processing system including a management system that manages a program that analyzes at least one of light intensity data and fluorescent label intensity data obtained by irradiating light onto a biological sample, and an analysis server that deploys and / or executes the program.

[0029] An example configuration of an information processing system according to an embodiment of the present technology will be described with reference to Fig. 5. Fig. 5 is a block diagram showing an example configuration of an information processing system 100 according to an embodiment of the present technology.

[0030] As shown in Fig. 5, the information processing system 100 includes a management system 70. This management system 70 manages a program that analyzes at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light, and an analysis server 101 that deploys and / or executes the program. Note that, although one analysis server 101 is shown in this configuration example, there may be multiple analysis servers 101. Furthermore, an analysis server system configured with multiple analysis servers 101 may also be used.

[0031] The inclusion of this management system 70 allows for centralized management of the programs and analysis server 101 included in the server system 10, making it possible to deploy programs regardless of whether the programs and analysis server 101 are in a cloud environment or an on-premise environment. A specific configuration example of this management system 70 will be described later.

[0032] The information processing system 100 further includes a biological sample analyzer 40, a data acquisition client terminal 30, a server system 10, and a data analysis client terminal 20. The biological sample analyzer 40 may be, for example, the flow cytometer described above. The data acquisition client terminal 30 acquires light intensity data of the biological sample from the biological sample analyzer 40. The server system 10 primarily analyzes at least one of the light intensity data and the fluorescent label intensity data. The data analysis client terminal 20 also analyzes at least one of the light intensity data and the fluorescent label intensity data, specifically by sending analysis requests to the server system 10 and displaying the analysis results of the server system 10.

[0033] The management system 70 and server system 10 may be connected to each other via an information and communication network 50. The data analysis client terminal 20 and the data acquisition client terminal 30 may each be connected to the server system 10, for example, by wire or wirelessly, or may be connected via an information and communication network. The biological sample analyzer 40 may be connected to the data acquisition client terminal 30, for example, by wire or wirelessly.

[0034] (3) Management System The management system 70 manages a program for analyzing at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light, and an analysis server 101 for deploying and / or executing the program. The program and the analysis server 101 can be included in the server system 10 described above.

[0035] The management system 70 may be a centralized management system in which programs and data are centrally managed by a specific server, or may be a system using distributed ledger technology (blockchain technology) in which multiple nodes (computers) participating in a network record and share data. The following description will discuss an example in which the management system 70 is a centralized management system. The management system 70 includes a resource management unit 71, a program management unit 72, and a connection unit 73.

[0036] (3-1) Resource Management Unit The resource management unit 71 is a service that manages resource information related to the computing resources of the analysis server 101. This resource information can be managed using, for example, a database. This database will be described with reference to Fig. 6. Fig. 6 is an example of a database managed by the resource management unit 71 according to an embodiment of the present technology.

[0037] As shown in FIG. 6, this database is composed of columns such as "server ID," "group ID," "server name," "server URL," "server type," "server specs," "connection status," and "usage status."

[0038] The “server ID” is an ID for uniquely identifying the analysis server 101 registered in the server system 10 .

[0039] The "group ID" is an ID for identifying a group to which the user who owns the corresponding analysis server 101 belongs. For example, a group ID may be assigned to each company to which the user belongs.

[0040] “Server name” is the name of the analysis server 101 .

[0041] "Server URL" is information indicating the location of the analysis server 101 on the information communication network.

[0042] The "server type" is information for identifying the environment in which the resources of the corresponding analysis server 101 exist. Examples of the "server type" include "Cloud On-Demand," "Cloud Dedicated," and "On-Premise."

[0043] "Cloud On-Demand" is a format in which the analysis server 101 exists within a public cloud network, and the user secures computing resources on demand. Securing computing resources on demand means that resources are secured only when needed, and only in the amount needed, rather than being secured all the time.

[0044] "Cloud Dedicated" is a format in which the analysis server 101 exists within a public cloud network, and the user always secures computing resources.

[0045] "On-Premise" is a format in which the analysis server 101 exists within an on-premise network.

[0046] “Server specifications” is information about the specifications of the analysis server 101 .

[0047] "Connection status" indicates whether the data analysis client terminal 20 is connected to the analysis server 101. "Online" indicates that the data analysis client terminal 20 is connected to the analysis server 101.

[0048] "Usage status" indicates whether a user is using the analysis server 101. "In-use" indicates a situation in which a specific user is using the analysis server 101. "Idle" indicates a situation in which no user is using the analysis server 101.

[0049] By managing such resource information with the resource management unit 71, the user can flexibly specify computing resources that meet their needs. As a specific example, an analysis execution request from the data analysis client terminal 20 can include information such as "Perform analysis using an analysis server that is owned by a user belonging to the user group 100, is operating within an on-premise network, is not currently in use, and has specifications above a certain level."

[0050] The resource management unit 71 can manage not only the resources of the analysis server 101, but also resources related to data storage and databases. In this case, it is possible to create multiple resource management tables for each type of resource to be managed, or to expand the relevant table to enable management of multiple resource types. This allows for a flexible system configuration, for example, by creating data storage in an on-premise network and executing analysis processing on the analysis server 101 in a public cloud network.

[0051] The data analysis client terminal 20 only needs to connect to the connection destination of the analysis server 101 returned from the management system 70. Therefore, the data analysis client terminal 20 can perform analysis processing without being aware of the physical location of the computing resources.

[0052] (3-2) Program Management Unit The program management unit 72 is a service that manages program information related to a program to be analyzed. This program information can be managed using, for example, a database. This database will be described with reference to FIG. 7. FIG. 7 is an example of a database managed by the program management unit 72 according to an embodiment of the present technology.

[0053] As shown in FIG. 7, this database is made up of columns such as "program version," "I / F version," "program URL," and "tag."

[0054] "Program version" is information about the version of a program. It is assumed that the program version is managed uniquely for each program. The program version may be managed incrementally using a single-digit number, or may be managed using a multi-digit version in a format consisting of a major version, a minor version, and a maintenance version.

[0055] "I / F version" is information for managing the version of the interface between the server and the client. "I / F version" may be, for example, the version of the API (Application Programming Interface).

[0056] The "program URL" is information indicating the location on the information communication network where the program is stored. For example, an agent unit (described later) can obtain the program based on this information and deploy the program on a predetermined analysis server 101.

[0057] A "tag" is information that indicates the attributes or characteristics of a program. For example, "latest" indicates that this program is the latest version.

[0058] The program management unit 72 manages such program information, enabling flexible system construction. As a specific example, an analysis execution request from the data analysis client terminal 20 can include information such as "Among programs with a specified I / F version, execute analysis using a program with the latest program version."

[0059] The program management unit 72 may manage multiple programs depending on the analysis content. In this case, multiple databases for managing the programs can be constructed, and the databases can be expanded.

[0060] (3-3) Connection Unit The connection unit 73 connects to at least one of a system and a device different from the management system 70. In the configuration example shown in Fig. 5, the connection unit 73 connects to each of the data acquisition client terminal 30, the server system 10, and the data analysis client terminal 20.

[0061] The connection unit 73 receives an analysis execution request from the data analysis client terminal 20, selects and secures an appropriate analysis server 101, selects an appropriate program, and deploys the program on the analysis server 101. Furthermore, the connection unit 73 notifies the data analysis client terminal 20 of the connection destination of the analysis server 101. These operations are realized in cooperation with the resource management unit 71, the program management unit, and the agent unit 80 (described later), etc.

[0062] The connection unit 73 can select an analysis server 101 having appropriate computing performance depending on the size of the data to be analyzed (number of events, number of dimensions), for example.

[0063] (4) Server System The server system 10 includes an agent unit 80 and an analysis server 101 .

[0064] [(4-1) Agent Unit] The management system 70 and the server system 10 may be connected to different information and communication networks. The management system 70 may be connected to a first information and communication network, and the server system 10 may be connected to a second information and communication network. The first information and communication network and the second information and communication network may be connected to each other via the communication processing unit 60.

[0065] The communication processing unit 60 may be, for example, a router, etc. A router has a firewall function that blocks specific communications, and therefore can protect the server system 10 from unauthorized access, malware, etc.

[0066] The management system 70, which centrally manages the servers and programs, is preferably connected to a public cloud network. That is, the first information and communication network may be the public cloud network. This allows the management system 70 to be accessed from the server system 10.

[0067] On the other hand, mainly for security reasons, the server system 10 may be connected to an on-premises network. That is, the second information and communication network may be a private cloud network or an on-premises network. In this case, communication from the server system 10 to the management system 70 is possible, but communication from the management system 70 to the server system 10 is blocked by the communication processing unit 60.

[0068] Therefore, it is preferable that a program that serves as the origin of communication to the management system 70 exists within the on-premise network. The information processing system according to an embodiment of the present technology further includes an agent unit 80 that connects to the analysis server 101 and the connection unit 73. The agent unit 80 connects to a second information communication network. The agent unit 80 has the extremely important function of linking the management system 70 and the analysis server 101. The presence of the agent unit 80 makes it possible to manage the analysis server 101 regardless of whether the analysis server 101 is connected to a public cloud network or an on-premise network.

[0069] The agent unit 80 may be a resident program installed on any computer connected to the second information communication network. The agent unit 80 includes a resource registration unit 81. The resource registration unit 81 transmits resource information of the analysis server 101 to the resource management unit 71 via a connection unit 73 included in the management system 70. This allows the resource management unit 71 included in the management system 70 to manage resource information of the analysis server 101 located within, for example, an on-premise network.

[0070] The agent unit 80 also includes a system construction unit 82. The system construction unit 82 deploys and / or executes the program to be analyzed on the analysis server 101. The processing flow at this time will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the processing flow of the information processing system 100 according to an embodiment of the present technology.

[0071] As shown in FIG. 8, first, in step S101, the data analysis client terminal 20 transmits analysis information regarding the analysis process of at least one of the light intensity data and the fluorescent label intensity data to the connection unit 73 in an analysis execution request.

[0072] Next, in step S102, the connection unit 73 determines a program to perform the analysis processing and an analysis server 101 that will deploy and / or execute the program based on at least one of the analysis information, resource information, and program information. The program information related to the program is managed by the program management unit 72. The resource information related to the analysis server 101 is managed by the resource management unit 71.

[0073] Next, in step S103, the connection unit 73 transmits information about the determined analysis server 101 and program to the system construction unit 82.

[0074] Next, in step S104, the system construction unit 82 accesses the computer in which the program is stored based on the information about the program, and acquires the program.

[0075] Next, in step S105, the system construction unit 82 deploys the acquired program in a predetermined analysis server 101 based on the information about the analysis server 101. In this way, the server system 10 can be constructed.

[0076] Next, in step S106, the connection unit 73 transmits information for connecting to the analysis server 101 to the data analysis client terminal 20. That is, the connection unit 73 transmits information about the analysis server 101 that deploys and / or executes a program to the data analysis client terminal 20.

[0077] Finally, in step S107, the data analysis client terminal 20 connects to the analysis server 101 based on the information for connecting to the analysis server 101. This allows the data analysis client terminal 20 to analyze at least one of the light intensity data and the fluorescent label intensity data.

[0078] When the analysis process is completed, the data in the analysis server 101 may be deleted, thereby preventing unauthorized access to the data.

[0079] In this example of the processing flow, the system construction unit 82 deploys the program within the analysis server 101, but the program may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, the system construction unit 82 can execute a predetermined program from among the different programs. This reduces the time required to deploy the program when an analysis execution request is received.

[0080] The system construction unit 82 can install programs not only on computers connected to the on-premise network but also on computers connected to the public cloud network. This allows the analysis server 101 connected to the public cloud network to be registered in the management system 70. In this case, in cases where computation resources are secured on demand in response to an analysis execution request from the data analysis client terminal 20, executable programs can generally be specified when the analysis server 101 is started.

[0081] (4-2) Client-Server Communication Communication between the management system 70 and the agent unit 80 is performed as client-server communication between the management system 70, which is the server, and the agent unit 80, which is the client. In client-server communication, a response is usually returned from the server in response to a request from the client. For example, in the resource registration process described above, the agent unit 80, which is the client, sends a request to the management system 70, and the management system 70 executes the necessary processing in response to this request.

[0082] On the other hand, there are cases where communication to a client originating from the management system 70, which is a server, is required. In such cases, communication is performed from the management system 70 in the public cloud network to the agent unit 80 in the on-premise network. Therefore, considering the existence of the communication processing unit 60, there are technical challenges in how to achieve this.

[0083] Generally, communication initiated by a server to a client is called server push, and several technologies exist for this, such as polling, long polling (COMET), and WebSocket. WebSocket is a technology that allows for two-way communication, but it also requires communication outside the framework of the HTTP (HTTPS) protocol. Therefore, considering the existence of HTTP proxies, there are issues with its communication capabilities.

[0084] In normal client-server communication, the client requests data from the server, and the server returns the data accordingly. However, if the server needs to send data constantly, the client must periodically request the data from the server. This is called polling.

[0085] Polling has the advantage of being able to receive data from the server at all times, but the disadvantage is that it places a heavy load on the server. Also, network communication occurs every time the client sends a data request to the server, consuming bandwidth.

[0086] Long polling can improve these disadvantages of polling. Long polling is a type of client-server communication in which a server periodically sends data to a client. Long polling is suitable for communication between the management system 70 and the agent unit 80.

[0087] Long polling will be described with reference to Fig. 9. Fig. 9 is a schematic diagram showing an example of a processing flow of long polling. As shown in Fig. 9, in long polling, a client (in this embodiment, the agent unit 80) sends an HTTP request to a server (in this embodiment, the management system 70) and then waits for data from the server. When the data is updated, the server sends the data to the client.

[0088] Long polling has the advantage of reducing the load on the server and saving bandwidth. Furthermore, long polling improves the latency between when the server receives data to be notified to the client and when it returns a response to the client, compared to polling. Furthermore, unlike WebSocket, long polling is suitable for communication between the management system 70 and the agent unit 80 because communication is performed only within the HTTP (HTTPS) protocol. Therefore, it is preferable for the agent unit 80 to communicate with the connection unit 73 using long polling. Note that the communication method is not limited to long polling.

[0089] An example of a case where a server push from the management system 70 to the agent unit 80 is required is processing when an analysis execution request using the analysis server 101 is received from the data analysis client terminal 20. An analysis execution request accepted by the connection unit 73 of the management system 70 is notified by server push to an appropriate analysis server 101 depending on the content of the request. The agent unit 80 acquires a necessary program depending on the content of the request, deploys it on the analysis server 101, executes automatic analysis processing, starts interactive analysis processing, and waits for a connection from the data analysis client terminal 20. The data analysis client terminal 20 connects to the connection destination of the analysis server 101 returned from the connection unit 73, and acquires automatic analysis results, executes interactive analysis processing, etc.

[0090] (4-3) Analysis Server The analysis server 101 performs analysis processing in response to requests from the data analysis client terminal 20. Since there is a large amount of data from the biological sample analyzer and there are limits to the amount of data that can be analyzed within the data analysis client terminal 20, it is preferable to perform the analysis within the analysis server 101.

[0091] The analysis server 101 has a plurality of services. In this configuration example, the analysis server 101 has services such as an automatic analysis processing unit 11, an interactive analysis processing unit 12, an output data generation unit 13, a connection unit 14, an optical data storage unit 15, an analysis result data storage unit 16, and a database 17. These services can be realized by the agent unit 80 deploying programs.

[0092] In one embodiment of the present disclosure, the automatic analysis processing unit 11 may calculate fluorescent label intensity data from light intensity data acquired by irradiating a biological sample with light. The light intensity data may be light intensity data transmitted from the data acquisition client terminal 30 to the analysis server 101. The light intensity data may be stored in the light data storage unit 15. The automatic analysis processing unit 11 may acquire the light intensity data from the light data storage unit 15.

[0093] The automatic analysis processing unit 11 calculates fluorescent label intensity data by performing, for example, a fluorescence correction process or an unmixing process on the light intensity data. The unmixing process is also called a fluorescence separation process.

[0094] The automatic analysis processing unit 11 preferably performs the unmixing process using spectral reference data. The spectral reference data used in the unmixing process includes spectral data of fluorescence generated when a predetermined excitation light is irradiated on a fluorescent dye labeling a particle. The spectral reference data used in the unmixing process may include spectral data of fluorescence generated when light having a predetermined wavelength is irradiated on the fluorescent dye labeling a particle, and spectral data of fluorescence generated when light having a wavelength different from the predetermined wavelength is irradiated on the fluorescent dye labeling a particle.

[0095] The spectral reference data may be stored in advance in any storage unit or database within the analysis server 101, for example, in the database 17. The automatic analysis processing unit 11 may acquire the spectral reference data, for example, from the database 17, and then perform the unmixing process using the acquired spectral reference data.

[0096] The automatic analysis processing unit 11 performs an analysis process on the fluorescent label intensity data. The automatic analysis processing unit 11 generates analysis result data through the analysis process. Output data can be generated from the analysis result data. The output data is transmitted to the data analysis client terminal 20, and the data analysis client terminal 20 then causes an output device to output the output data. The output device can be, for example, a display device. The output device can be configured to allow a user to input analysis commands, which will be described later.

[0097] In this specification, "analysis result data" refers to data generated by the analysis process in the analysis server 101. "Output data" is a part of the analysis result data, and is particularly data used to output the analysis results in the data analysis client terminal 20.

[0098] The automatic analysis processing unit 11 preferably executes a process of calculating fluorescent labeled intensity data from the light intensity data in response to the light intensity data being stored in the optical data storage unit 15. The automatic analysis processing unit 11 may then analyze the fluorescent labeled intensity data to generate analysis result data. Furthermore, the automatic analysis processing unit 11 may generate output data from the analysis result data. For example, the automatic analysis processing unit 11 may start the automatic analysis process in response to the light intensity data being stored in the optical data storage unit 15. In other words, the automatic analysis processing unit 11 may execute an event-driven analysis process triggered by the storage.

[0099] The automatic analysis processing unit 11 secures computation resources for automatic analysis processing in response to the storage of light intensity data in the optical data storage unit 15. That is, the automatic analysis processing unit 11 treats the storage as receipt of an analysis start command, and in response to the receipt, can secure computation resources within the analysis server 101. The automatic analysis processing unit 11 can use the secured computation resources to perform calculation processing of fluorescent labeled intensity data, analysis processing of the fluorescent labeled intensity data, and generation processing of output data from the analysis result data.

[0100] The interactive analysis processing unit 12 can analyze the fluorescent label intensity data based on an analysis command for the output data output to the output device and generate analysis result data. The output data may be output data generated by the automatic analysis processing unit 11, or may be output data acquired or generated by the output data generation unit 13 described below.

[0101] The interactive analysis processing unit 12 may execute a process of calculating fluorescent label intensity data from the light intensity data. The calculated fluorescent label intensity data may then be analyzed based on the analysis command to generate analysis result data. The interactive analysis processing unit 12 may then generate output data from the generated analysis result data.

[0102] The interactive analysis processing unit 12 may secure a computation resource for processing by the interactive analysis processing unit 12 in response to receiving an analysis start command. After securing the computation resource, the interactive analysis processing unit 12 waits until an analysis command is sent from the data analysis client terminal 20. As described above, the automatic analysis processing unit 11 secures a computation resource for processing by the automatic analysis processing unit in response to receiving an analysis start command, and the interactive analysis processing unit 12 may also secure a computation resource for processing by the interactive analysis processing unit 12 in response to receiving an analysis start command. Therefore, in the present disclosure, the processing by the automatic analysis processing unit and the processing by the interactive analysis processing unit may be executed on different computation resources.

[0103] In response to receiving an analysis command transmitted from the data analysis client terminal 20, the interactive analysis processing unit 12 may execute a process for calculating fluorescent label intensity data, a process for analyzing the fluorescent label intensity data, and a process for generating output data from the analysis result data. These processes may be event-driven analysis processes triggered by the reception of the analysis command. In other words, the interactive analysis process according to the present technology may be an event-driven analysis process.

[0104] The interactive analysis processing unit 12 may perform the calculation process of fluorescent label intensity data, the analysis process of fluorescent label intensity data, and the generation process of output data from the analysis result data in the same manner as these processes performed by the automatic analysis processing unit 11.

[0105] The connection unit 14 is a functional element for executing a remote procedure call (RPC) in interactive processing between the analysis server 101 (particularly the interactive analysis processing unit 12) and the data analysis client terminal 20. For example, the connection unit 14 causes the analysis server 101 to execute an analysis command input at the data analysis client terminal 20.

[0106] The output data generation unit 13 can generate output data from the analysis result data stored in the analysis result data storage unit 16. Then, the output data generation unit 13 transmits the output data to the data analysis client terminal 20.

[0107] The computational resources required for processing by the output data generation unit 13 are small, which makes it possible to reduce the operating costs of the analysis server 101.

[0108] The processing by the output data generation unit 13 may be executed by a constantly running virtual server in the analysis server 101. By having the virtual server constantly running, the output data acquisition process can be executed at high speed without the waiting time associated with starting up the server. Furthermore, the output data generation unit 13 may be configured as a serverless architecture.

[0109] The light data storage unit 15 stores light intensity data and / or fluorescent label intensity data. The light data storage unit 15 may include two storage units: a light intensity data storage unit that stores light intensity data, and a fluorescent label intensity data storage unit that stores fluorescent label intensity data.

[0110] The analysis result data storage unit 16 stores analysis result data generated by the automatic analysis processing unit 11 based on the fluorescent label intensity data and / or analysis result data generated by the interactive analysis processing unit 12 based on the fluorescent label intensity data. Furthermore, the analysis result data storage unit 16 stores output data generated from each of these pieces of analysis result data.

[0111] The analysis server 101 may be configured as a single server device, or may be configured as a system configured from multiple server devices. The multiple server devices may be located in a single data center, or may be distributed across multiple data centers located in different locations or countries.

[0112] An example of the hardware configuration of the analysis server 101 will be described with reference to Fig. 10 . Fig. 10 is a block diagram showing an example of the configuration of the analysis server 101 according to an embodiment of the present technology. As shown in Fig. 10 , the analysis server 101 includes a CPU (Central Processing Unit) 1001, a RAM 1002, and a ROM 1003. The CPU 1001, the RAM 1002, and the ROM 1003 are connected to each other via a bus 1004. An input / output interface 1005 is further connected to the bus 1004.

[0113] The input / output interface 1005 is connected to a communication device 1006 , a storage device 1007 , a drive 1008 , an output unit 1009 , and an input unit 1010 .

[0114] The communication device 1006 connects the analysis server 101 to the network 1011 via a wired or wireless connection. The communication device 1006 allows the analysis server 101 to acquire various data (e.g., image data) via the network 1011. The acquired data can be stored in, for example, the storage device 1007. The type of communication device 1006 may be appropriately selected by a person skilled in the art.

[0115] The storage device 1007 can store an operating system, a program for causing the analysis server 101 to implement the information processing method according to the present disclosure, various other programs, image data, various data used in the information processing method according to the present disclosure, and various other data. The operating system may be, for example, a UNIX (registered trademark)-based OS, particularly LINUX (registered trademark), or a Windows (registered trademark)-based OS.

[0116] The drive 1008 can read data (e.g., light intensity data, fluorescent label intensity data, analysis result data, or output data) or programs recorded on a recording medium and output the data to the RAM 1003. The recording medium can be, for example, an HDD, an SSD, a microSD memory card, an SD memory card, or a flash memory, but is not limited to these.

[0117] An output device, for example, a display device, may be connected to the output unit 1009. The input unit 1010 can receive input for operating the analysis server 101.

[0118] [(5) Data Analysis Client Terminal] The data analysis client terminal 20 analyzes at least one of light intensity data and fluorescent label intensity data. An example configuration of the data analysis client terminal 20 will be described with reference to FIG. 11 . FIG. 11 is a block diagram showing an example configuration of the data analysis client terminal 20 according to an embodiment of the present technology. As shown in FIG. 11 , the data analysis client terminal 20 includes a processing unit 21, an analysis instruction unit 22, a connection unit 23, an output data storage unit 24, and a communication unit 25.

[0119] The processing unit 21 performs processing to output the output data transmitted from the analysis server 101 to an output device attached to the data analysis client terminal 20. In particular, the output data is displayed in a window on a screen displayed on the output device (particularly a display device). That is, the data analysis client terminal may include an output device to which the output data is output.

[0120] The analysis instruction unit 22 transmits a request to start the interactive analysis process described above to the analysis server 101 .

[0121] The analysis instruction unit 22 also accepts input of an analysis command used in the interactive analysis process described above, and transmits the analysis command to the analysis server 101. The analysis command may include the worksheet setting data described above. The interactive analysis processing unit 12 executes the analysis process by referring to the worksheet setting data, thereby generating output data according to the worksheet setting data. In this manner, the data analysis client terminal according to the present disclosure may be configured to transmit the analysis command for the output data output to the output device to the analysis server 101. The data analysis client terminal according to the present disclosure may also be configured to cause the output device to output a window displaying the output data, and to accept input of the analysis command in the window.

[0122] The connection unit 23 is a functional element for executing an RPC (Remote Procedure Call) in interactive processing between the analysis server 101 (particularly the interactive analysis processing unit 12) and the data analysis client terminal 20 (particularly the analysis instruction unit 22). For example, a combination of the connection unit 23 of the data analysis client terminal 20 and the connection unit 14 of the analysis server 101 may enable an analysis command input at the data analysis client terminal 20 to be transmitted to the analysis server 101 and executed at the analysis server 101.

[0123] The output data storage unit 24 stores the output data transmitted from the analysis server 101 .

[0124] The communication unit 25 receives, from the analysis server 101, output data that the analysis server 101 has created based on the fluorescent label intensity data.

[0125] The hardware configuration of the data analysis client terminal 20 will be described with reference to Fig. 12. Fig. 12 is a block diagram showing an example configuration of the data analysis client terminal 20 according to an embodiment of the present technology. Note that the terminal may be, for example, a general-purpose information processing device (particularly, a computer).

[0126] 12 includes a CPU (Central Processing Unit) 1101, a RAM 1102, and a ROM 1103. The CPU 1101, the RAM 1102, and the ROM 1103 are connected to one another via a bus 1104. An input / output interface 1105 is further connected to the bus 1104.

[0127] The input / output interface 1105 is connected to a communication device 1106 , a storage device 1107 , a drive 1108 , an output unit 1109 , and an input unit 1110 .

[0128] The communication device 1106 connects the information processing device 1100 to the network 1111 via a wired or wireless connection. The communication device 1106 allows the information processing device 1100 to transmit or receive various data via the network 1111. For example, the communication device 1106 transmits various data to the server system 10 or receives various data from the server system 10. The type of the communication device 1106 may be appropriately selected by one skilled in the art.

[0129] The storage device 1107 may store an operating system, a program for causing the output data output unit to output output data, a program for implementing interactive analysis processing, and various other programs, as well as various data used in information processing according to the present disclosure. The operating system may be, for example, a UNIX (registered trademark)-based OS, particularly LINUX (registered trademark), or a Windows (registered trademark)-based OS.

[0130] The drive 1108 can read data (e.g., output data) or programs recorded on a recording medium and output the data to the RAM 1103. The recording medium can be, for example, an HDD, an SSD, a microSD memory card, an SD memory card, or a flash memory, but is not limited to these.

[0131] The output unit 1109 outputs output data to an output device. The output device may be, for example, a display device. The input unit 1110 accepts input of analysis commands, for example, in interactive analysis processing. An input device such as a keyboard or a mouse may be connected to the input unit 1110, and the analysis commands can be input via these input devices.

[0132] The data analysis client terminal 20 (particularly the processing unit 21) outputs the output data to an output device. An example of the output data output to the output device is shown in Fig. 13. Fig. 13 is a diagram showing an example of a window that the data analysis client terminal 20 according to an embodiment of the present technology causes the output device to output.

[0133] As shown in FIG. 13 , a window displaying output data is displayed on the output device. Seven plot images are displayed in the lower left of the window. Furthermore, one clustering image is displayed to the right of the window. Furthermore, statistical data (number of events, Parent %, and Total %) corresponding to each gate is displayed in the upper left of the window. In this manner, image data and / or statistical data based on the output data can be displayed in the window. The image data may include one or more plot images and / or one or more clustering images as described above. Furthermore, the statistical data may include one or more statistics.

[0134] [(6) Data Acquisition Client Terminal] The data acquisition client terminal 30 will be described with reference to Fig. 14. Fig. 14 is a block diagram showing an example configuration of the data acquisition client terminal 30 according to an embodiment of the present technology. As shown in Fig. 14, the data acquisition client terminal 30 includes a data acquisition unit 31, a transmission unit 32, a data processing unit 33, and a data storage unit 34.

[0135] The data acquisition unit 31 acquires the measurement data transmitted from the biological sample analyzer 40. The measurement data includes light intensity data that is the subject of processing by the automatic analysis processing unit 11. The light intensity data may be light intensity data acquired by irradiating a biological sample with light.

[0136] The transmitting unit 32 transmits the measurement data (including light intensity data) acquired by the data acquiring unit 31 or the measurement data processed by the data processing unit 33 described below to the analysis server 101 (particularly, the light data storage unit 15 of the analysis server 101). The transmitting unit 32 may transmit analysis setting data in addition to the measurement data to the analysis server 101. Preferably, the transmitting unit 32 transmits the light intensity data, or the light intensity data and the analysis setting data, to the analysis server 101 in response to acquiring the light intensity data. For example, the transmitting unit 32 may automatically start transmitting the measurement data or the processed measurement data (and the analysis setting data) in response to acquiring the measurement data. In this way, a data client terminal according to the present disclosure may transmit the light intensity data to the analysis server 101. Furthermore, a data acquisition client terminal according to the present disclosure may be configured to transmit the light intensity data (and the analysis setting data) to the analysis server 101 in response to acquiring the light intensity data.

[0137] Furthermore, in one embodiment of the present disclosure, the data acquisition client terminal 30 may execute a calculation process to calculate the fluorescent label intensity data from the light intensity data. The calculation process may be executed as described in (3-1) above, and may be, for example, a fluorescence correction process or an unmixing process. In this embodiment, the transmission unit 32 may transmit the fluorescent label intensity data (or the fluorescent label intensity data after processing by the data processing unit 33 described below) to the analysis server 101 (particularly, the optical data storage unit 15 of the analysis server 101). In this manner, the data client terminal according to the present disclosure may transmit the fluorescent label intensity data to the analysis server 101. Furthermore, the data acquisition client terminal according to the present disclosure may be configured to transmit the fluorescent label intensity data to the analysis server 101 in response to acquiring the fluorescent label intensity data.

[0138] In the present disclosure, the transmitting unit 32 may transmit both the measurement data and the fluorescent label intensity data to the analysis server 101 .

[0139] The data acquisition client terminal 30 can execute the data acquisition process and the upload process separately by having a functional unit called a transmission unit 32 in addition to the data acquisition unit 31. This makes it possible to upload measurement data (including light intensity data), fluorescent label intensity data calculated from the measurement data, or both of these data to the analysis server 101 without affecting the data acquisition process from the biological sample analyzer 40.

[0140] The data processing unit 33 can perform predetermined processing on the measurement data and / or fluorescent labeled intensity data acquired by the data acquisition unit 31. This processing may be compression processing or data processing (e.g., format conversion processing). This data processing can convert the measurement data and / or fluorescent labeled intensity data into a format suitable for information processing in the analysis server 101, thereby improving the efficiency of processing in the analysis server 101. In this way, the data acquisition client terminal according to the present disclosure may be configured to perform predetermined processing on the light intensity data or the fluorescent labeled intensity data in response to acquiring the light intensity data or the fluorescent labeled intensity data, and then transmit the processed light intensity data or the fluorescent labeled intensity data to the analysis server 101.

[0141] The data storage unit 34 can store the measurement data or the processed measurement data. The data storage unit 34 may store the fluorescent label intensity data or the processed fluorescent label intensity data.

[0142] The same applies to the hardware configuration example of the data acquisition client terminal 30 as described for the data analysis client terminal 20. The data acquisition client terminal 30 may also be, for example, a general-purpose information processing device (particularly, a computer).

[0143] (7) Biological Sample Analyzer The biological sample analyzer may be, for example, a flow cytometer as described above, but is not limited to this. An example configuration of the biological sample analyzer will be described with reference to Fig. 15. Fig. 15 is a schematic diagram showing an example configuration of a biological sample analyzer 40 according to one embodiment of the present technology.

[0144] 15 , the biological sample analyzer 40 includes a light irradiation unit 41 that irradiates light onto the biological sample S flowing through a flow path C, a detection unit 42 that detects the light generated by the irradiation, and an information processing unit 43 that processes information related to the light detected by the detection unit. Examples of the biological sample analyzer 40 include a flow cytometer and an imaging cytometer. The biological sample analyzer 40 may also include a fractionation unit 44 that separates specific biological particles P from within the biological sample. An example of a biological sample analyzer 40 that includes a fractionation unit is a cell sorter.

[0145] [(7-1) 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 non-cellular biological particles include extracellular vesicles, particularly exosomes and microvesicles. The biological particles may be labeled with one or more labeling substances (e.g., dyes (particularly fluorescent dyes) and fluorescent dye-labeled antibodies). Note that the biological sample analyzer of the present disclosure may also analyze particles other than biological particles, such as beads for calibration purposes.

[0146] [(7-2) Flow Channel] The flow channel C can be configured to allow a biological sample to flow, particularly 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 can be designed to form a laminar flow, particularly a laminar flow in which the flow of the biological sample (sample flow) is enveloped by the flow of sheath liquid. The design of the flow channel structure can be appropriately selected by those skilled in the art, and a known design may be adopted. The flow channel C can be formed in a flow channel structure (particularly a flow channel structure in which focusing is performed) 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 can 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 can be formed from materials such as plastic or glass.

[0147] The device of the present disclosure may be configured so that the light from the light irradiation unit is irradiated onto the biological sample flowing through the flow path C, particularly onto biological particles in the biological sample. The device 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 the 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 the 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), and an example of such a configuration is a jet-in-air flow cytometer.

[0148] [(7-3) Light Irradiation Unit] The light irradiation unit 41 includes a light source unit that emits light and a light-guiding optical system that guides the light to the flow path C. The light source unit includes one or more light sources. The type of light source may be, 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. The biological sample may be irradiated with light at one or more points. The light irradiation unit 41 may be configured to focus light irradiated from one or more different light sources at one irradiation point.

[0149] [(7-4) Detector] The detector 42 includes at least one photodetector that detects light generated by the light irradiation unit irradiating particles 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, e.g., 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 detector may also include an imaging element such as a CCD or CMOS. The detector can acquire images of the bioparticles (e.g., bright-field images, dark-field images, and fluorescence images) using the imaging element.

[0150] The detection unit 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 may be configured, for example, to separate light from bioparticles and detect light of different wavelength ranges using multiple photodetectors, the number of which is greater than the number of fluorescent dyes. A flow cytometer including such a detection optical system is called a spectral flow cytometer. Furthermore, the detection optical system may be configured, for example, to separate light from the light from the bioparticles into light corresponding to the fluorescent wavelength range of the fluorescent dye, and to detect the separated light using the corresponding photodetector.

[0151] The detection unit 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 an information processing unit. The digital signal may be treated by the information processing unit 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).

[0152] (7-5) Information Processing Unit The information processing unit 43 includes, for example, a processing unit that processes various data (for example, optical data) and a storage unit that stores various data.

[0153] If the biological sample analyzer includes a fractionating unit (described below), the information processing unit can determine whether to fractionate bioparticles based on the optical data and / or morphological information. The information processing unit can then control the fractionating unit based on the results of this determination, allowing the fractionating unit to fractionate the bioparticles.

[0154] The information processing unit 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 may be included in a housing that includes the light irradiation unit and the detection unit, or may be located outside the housing. The information processing unit may be realized by, for example, the data acquisition client terminal 30.

[0155] [(7-6) Sorting Unit] The sorting unit 44 can sort bioparticles, for example, according to the determination result by the information processing unit. 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 bioparticles within a flow channel structure to perform sorting. The flow channel structure may be provided with a control mechanism using, for example, pressure (spray or suction) or electric charge. An example of such a flow channel structure is a chip (e.g., the chip described in JP 2020-76736 A) having a flow channel structure in which a flow channel C branches downstream into a recovery flow channel and a waste flow channel, and specific bioparticles are recovered into the recovery flow channel.

[0156] The biological sample analyzing device 40 may be, for example, a microscope device, particularly a fluorescence microscope device, for performing multicolor fluorescence imaging. In recent years, the number of fluorophores used in fluorescence imaging has also tended to increase, and the information processing system of the present disclosure may be executed on light intensity data acquired by the microscope device.

[0157] The above description of the information processing system according to the first embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0158] [2. Second Embodiment of the Present Technology (Example 2 of Information Processing System)] When determining a program and an analysis server 101 to perform analysis processing, instead of or in addition to analysis information, the connection unit 73 may determine the program and the analysis server 101 to perform analysis processing based on information related to a usage fee for the analysis server 101. That is, the connection unit may determine the program to perform the analysis processing and the analysis server 101 that deploys and / or executes the program based on at least one of the analysis information, the resource information, the program information, and information related to a usage fee for the analysis server 101, and transmit information related to the determined analysis server 101 and the program to the system construction unit.

[0159] An example of the processing flow at this time will be described with reference to Fig. 8 again. In step S102, the connection unit 73 determines the analysis server 101 and the program. At this time, the connection unit 73 can determine the program that will perform this analysis processing and the analysis server 101 that will deploy and / or execute this program based on at least one of the analysis information, the resource information, the program information, and information related to the usage fee for the analysis server 101.

[0160] According to this embodiment, the operating costs of the analysis server 101 can be reduced. The analysis server 101 with high resource performance tends to have a high usage fee. Therefore, if an analysis process that does not require high resource performance is performed by an analysis server 101 with high resource performance, the cost performance will decrease. Therefore, by determining the analysis server 101 based on at least one of the analysis information, the resource information, the program information, and information regarding the usage fee for the analysis server 101, it is possible to achieve a balance between the operating costs and the processing time.

[0161] The above description of the information processing system according to the second embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0162] 3. Third Embodiment of the Present Technology (Example 3 of Information Processing System) A configuration example of an information processing system according to an embodiment of the present technology will be described with reference to Fig. 16. Fig. 16 is a block diagram showing a configuration example of an information processing system 100 according to an embodiment of the present technology.

[0163] 16 , the information processing system 100 may further include a data dividing unit 90. The data dividing unit 90 divides at least one of the light intensity data and the fluorescent label intensity data based on the resource information and transmits the divided data to different analysis servers (e.g., the first analysis server 10111, the second analysis server 10122, and the third analysis server 103). The data dividing unit 90 can divide the data by event, for example. This allows for shorter processing time than when a large amount of data is analyzed by a single analysis server 101.

[0164] In this configuration example, the server system 10 includes the data dividing unit 90, but the data dividing unit 90 may also be included in the communication processing unit 60, for example.

[0165] Although not shown, the data dividing unit 90 may divide, for example, the analysis result data or the output data.

[0166] The above description of the information processing system according to the third embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0167] 4. Fourth Embodiment of the Present Technology (Example 4 of Information Processing System)] At least one of the analysis server 101 and the program used in the analysis process may be determined by the connection unit 73, or may be determined by the user via the data analysis client terminal 20. An example of the processing flow at this time will be described with reference to Fig. 17. Fig. 17 is a flowchart showing an example of the processing flow of the information processing system 100 according to an embodiment of the present technology.

[0168] As shown in FIG. 17, first, in step S201, the data analysis client terminal 20 accepts the designation of at least one of the analysis server 101 and the program.

[0169] Next, in step S202, the data analysis client terminal 20 transmits the analysis information and information about at least one of the analysis server 101 and the program to the connection unit 73. The processing flow thereafter may be the same as the flowchart shown in FIG.

[0170] In step S201, when the designation of at least one of the analysis server 101 and the program is accepted, a list of the analysis servers 101 and the programs that are candidates for designation can be displayed on an output device included in the data analysis client terminal 20. An example of the display at this time will be described with reference to Fig. 18. Fig. 18 is a diagram showing an example of a window that the data analysis client terminal 20 according to an embodiment of the present technology causes the output device to output.

[0171] As shown in Fig. 18, a list of multiple analysis servers 101 and multiple programs is displayed. In the list of analysis servers 101, attribute information such as "server name," "server type," "server specifications," and "usage fee" is displayed. In the list of programs, attribute information such as "program version" and "I / F version" is displayed. Note that it is not necessary for both the analysis servers 101 and the programs to be displayed, and at least one of them may be displayed.

[0172] In the list of analysis servers 101, it is preferable that only the analysis servers 101 owned by the group to which the user belongs are displayed based on the "group ID." It is also preferable that only the analysis servers 101 that are not in use are displayed based on the "usage status."

[0173] The data analysis client terminal 20 may have a search function. For example, by allowing a search by server name or program version, a user can easily find the necessary program or server. For example, the search function can be enhanced by providing a text box for inputting the program version or server name, or by providing a filter function.

[0174] The data analysis client terminal 20 may also have a sorting function. For example, by sorting the servers in descending order of server specs or in descending order of usage fees, the user can easily find the necessary programs and servers.

[0175] The above description of the information processing system according to the fourth embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0176] 5. Fifth Embodiment of the Present Technology (Fifth Example of Information Processing System) The analysis server 101 may be connected to an on-premises network or a public cloud network. In the configuration example shown in Fig. 5, the analysis server 101 is connected to an on-premises network. A configuration example in which the analysis server 101 is connected to a public cloud network will be described with reference to Fig. 19. Fig. 19 is a block diagram illustrating an example of a configuration of an information processing system 100 according to an embodiment of the present technology.

[0177] 19 , of the services provided by the analysis server 101, the automatic analysis processing unit 11, the interactive analysis processing unit 12, the output data generation unit 13, and the connection unit 141 are connected to the public cloud network. Of the services provided by the analysis server 101, the connection unit 141, the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 are connected to the on-premises network. The analysis server connected to the public cloud network is defined as the first analysis server 1011. The analysis server connected to the on-premises network is defined as the second analysis server 1012.

[0178] This configuration means that data and databases reside within the on-premise network, preventing highly confidential measurement data from being accessed illegally or leaked.

[0179] The processing flow at this time will be described with reference to Fig. 20. Fig. 20 is a flowchart showing an example of the processing flow of the information processing system 100 according to an embodiment of the present technology.

[0180] As shown in FIG. 20, first, in step S301, the data analysis client terminal 20 transmits analysis information regarding the analysis process of at least one of the light intensity data and the fluorescent label intensity data to the connection unit 73 in an analysis execution request.

[0181] Next, in step S302, the connection unit 73 determines a program to perform the analysis processing and an analysis server that will deploy and / or execute the program based on at least one of the analysis information, resource information, and program information. The program information related to the program is managed by the program management unit 72. The resource information related to the analysis server is managed by the resource management unit 71.

[0182] Next, in step S303, the connection unit 73 transmits information about the determined analysis server and program to the system construction unit 82.

[0183] Next, in step S304, the system construction unit 82 accesses the computer in which the program is stored based on the information about the program, and acquires the program.

[0184] Next, in step S305, the system construction unit 82 deploys the acquired program in a predetermined analysis server based on the information about the analysis server, thereby constructing the server system 10.

[0185] Next, in step S306, the connection unit 73 transmits information for connecting to the first analysis server 1011 and the second analysis server 1012 to the data analysis client terminal 20.

[0186] Next, in step S307, the data analysis client terminal 20 connects to the first analysis server 1011 based on the information for connecting to the first analysis server 1011.

[0187] Next, in step S308, the data analysis client terminal 20 notifies the first analysis server 1011 (particularly the connection unit 141) of information for connecting to the second analysis server 1012.

[0188] Next, in step S309, the first analysis server 1011 (particularly the connection unit 141) sends a data information acquisition request to the second analysis server 1012. At this time, it is preferable that the agent unit 80 communicates with the connection unit 73 by long polling.

[0189] Finally, in step S310, the second analysis server 1012 (particularly the connection unit 142) transmits the data stored in the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 to the first analysis server 1011. This enables the data analysis client terminal 20 to analyze at least one of the light intensity data and the fluorescent label intensity data.

[0190] In this example of the processing flow, the system construction unit 82 deploys the program within the analysis server 101, but the program may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, the system construction unit 82 can execute a predetermined program from among the different programs.

[0191] The above description of the information processing system according to the fifth embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0192] 6. Sixth Embodiment of the Present Technology (Example 6 of Information Processing System) Another configuration example in which the analysis server 101 is connected to a public cloud network will be described with reference to Fig. 21. Fig. 21 is a block diagram showing an example of the configuration of an information processing system 100 according to an embodiment of the present technology.

[0193] 21 , of the services provided by the analysis server 101, the connection unit 141, the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 are connected to the public cloud network. Of the services provided by the analysis server 101, the automatic analysis processing unit 11, the interactive analysis processing unit 12, the output data generation unit 13, and the connection unit 142 are connected to the on-premises network. The analysis server connected to the public cloud network is defined as the first analysis server 1011. The analysis server connected to the on-premises network is defined as the second analysis server 1012.

[0194] The first analysis server 1011 connected to the public cloud network can increase or decrease resources depending on the usage status, and can therefore flexibly respond to sudden increases in data volume.

[0195] The processing flow at this time will be described with reference to Fig. 22. Fig. 22 is a flowchart showing an example of the processing flow of the information processing system 100 according to an embodiment of the present technology.

[0196] As shown in FIG. 22, first, in step S401, the data analysis client terminal 20 transmits analysis information relating to the analysis process of at least one of the light intensity data and the fluorescent label intensity data to the connection unit 73.

[0197] Next, in step S402, the connection unit 73 determines a program to perform the analysis processing and an analysis server that will deploy and / or execute the program based on at least one of the analysis information, resource information, and program information. The program information related to the program is managed by the program management unit 72. The resource information related to the analysis server is managed by the resource management unit 71.

[0198] Next, in step S403, the connection unit 73 transmits information about the determined analysis server and program to the system construction unit 82.

[0199] Next, in step S404, the system construction unit 82 accesses the computer in which the program is stored based on the information about the program, and acquires the program.

[0200] Next, in step S405, the system construction unit 82 deploys the acquired program in a predetermined analysis server based on the information about the analysis server, thereby constructing the server system 10.

[0201] Next, in step S406 , the connection unit 73 transmits information for connecting to the first analysis server 1011 and the second analysis server 1012 to the data analysis client terminal 20 .

[0202] Next, in step S407, the data analysis client terminal 20 connects to the second analysis server 1012 based on the information for connecting to the second analysis server 1012.

[0203] Next, in step S408, the data analysis client terminal 20 notifies the second analysis server 1012 (particularly, the connection unit 142) of information for connecting to the first analysis server 1011.

[0204] Next, in step S409 , the second analysis server 1012 (particularly the connection unit 142 ) connects to the first analysis server 1011 based on the information for connecting to the first analysis server 1011 .

[0205] Finally, in step S410, the second analysis server 1012 (particularly the connection unit 142) acquires the data stored in the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 in the first analysis server 1011. This allows the data analysis client terminal 20 to analyze at least one of the light intensity data and the fluorescent label intensity data.

[0206] In this example of the processing flow, the system construction unit 82 deploys the program within the analysis server 101, but the program may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, the system construction unit 82 can execute a predetermined program from among the different programs.

[0207] The above description of the information processing system according to the sixth embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0208] [7. Seventh Embodiment of the Present Technology (Example of Server System)] The present technology provides a server system that includes a system construction unit that deploys and / or executes, on an analysis server, a program that analyzes at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light, and at least one of the program and the analysis server is determined based on a database that stores information related to at least one of the program and the analysis server.

[0209] An example configuration of this server system will be described with reference to Fig. 5 again. As shown in Fig. 5, the server system 10 according to an embodiment of the present technology includes a system construction unit 82. This system construction unit 82 deploys and / or executes, on the analysis server, a program that analyzes at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light.

[0210] At least one of the program and the analysis server is determined based on a database that stores information about at least one of the program and the analysis server. This database can be centrally managed, for example, by the management system 70. Alternatively, this database may be configured using distributed ledger technology (blockchain technology) in which multiple nodes (computers) participating in a network record and share data.

[0211] The above description of the server system according to the seventh embodiment of the present technology can be applied to other embodiments of the present technology unless there is a particular technical contradiction.

[0212] The present disclosure may also be configured as follows: [1] An information processing system including a management system that manages a program for analyzing at least one of light intensity data and fluorescent label intensity data acquired by irradiating a biological sample with light, and an analysis server that deploys and / or executes the program. [2] The information processing system according to [1], wherein the management system comprises: a resource management unit that manages resource information related to computing resources of the analysis server; a program management unit that manages program information related to the program; and a connection unit that connects to at least one of a system and a device different from the management system. [3] The information processing system according to [2], further including an agent unit that connects to the analysis server and the connection unit. [4] The information processing system according to [3], wherein the management system connects to a first information and communication network, the agent unit connects to a second information and communication network, and the first information and communication network and the second information and communication network are connected to each other via a communication processing unit. [5] The information processing system according to [4], wherein the first information and communication network is a public cloud network, and the second information and communication network is a private cloud network or an on-premises network. [6] The information processing system according to any one of [3] to [5], wherein the agent unit communicates with the connection unit by long polling. [7] The information processing system according to any one of [3] to [6], wherein the agent unit comprises a resource registration unit that transmits resource information of the analysis server to the resource management unit. [8] The information processing system according to any one of [3] to [7], wherein the agent unit comprises a system construction unit that at least one of deploys and executes the program on the analysis server.[9] The information processing system according to [8], further comprising a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein the data analysis client terminal transmits analysis information relating to an analysis process of at least one of the light intensity data and the fluorescent label intensity data to the connection unit, wherein the connection unit determines the program that will perform the analysis process and the analysis server that will at least one of deploy and execute the program based on at least one of the analysis information, the resource information, and the program information, and transmits information about the determined analysis server and the program to the system construction unit, wherein the system construction unit at least one of deploys and executes the program on the analysis server based on the received information about the analysis server and the program.

[10] The information processing system according to [9], wherein the connection unit determines the program that will perform the analysis process and the analysis server that will at least one of deploy and execute the program based on at least one of the analysis information, the resource information, the program information, and information about a usage fee for the analysis server, and transmits information about the determined analysis server and the program to the system construction unit.

[11] The information processing system according to any one of [2] to

[10] , further comprising a data dividing unit that divides at least one of the light intensity data and the fluorescent label intensity data based on the resource information and transmits each of the data to a different analysis server.

[12] The information processing system according to any one of [2] to

[11] , further comprising a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein the connection unit transmits information about the analysis server that at least one of deploys and executes the program to the data analysis client terminal.

[13] The information processing system according to

[12] , wherein the data analysis client terminal accepts designation of at least one of the analysis server and the program, and transmits information about at least one of the analysis server and the program to the connection unit.

[14] A server system including a system construction unit that deploys and / or executes, on an analysis server, a program that analyzes at least one of light intensity data and fluorescent label intensity data obtained by irradiating a biological sample with light, wherein at least one of the program and the analysis server is determined based on a database that holds information regarding at least one of the program and the analysis server.

[0213] REFERENCE SIGNS LIST 10 Server system 20 Data analysis client terminal 30 Data acquisition client terminal 40 Biological sample analyzer 60 Communication processing unit 70 Management system 71 Resource management unit 72 Program management unit 73 Connection unit 80 Agent unit 81 Resource registration unit 82 System construction unit 90 Data division unit 100 Information processing system 101 Analysis server

Claims

1. An information processing system including a management system that manages a program that analyzes at least one of light intensity data and fluorescent label intensity data obtained by irradiating light onto a biological sample, and an analysis server that deploys and / or executes the program.

2. The information processing system of claim 1, wherein the management system comprises: a resource management unit that manages resource information regarding the computing resources of the analysis server; a program management unit that manages program information regarding the program; and a connection unit that connects to at least one of a system and a device different from the management system.

3. The information processing system according to claim 2, further comprising an agent unit connected to said analysis server and said connection unit.

4. The information processing system according to claim 3, wherein the management system is connected to a first information and communication network, the agent unit is connected to a second information and communication network, and the first information and communication network and the second information and communication network are connected to each other via a communication processing unit.

5. The information processing system according to claim 4, wherein the first information communication network is a public cloud network, and the second information communication network is a private cloud network or an on-premise network.

6. The information processing system according to claim 3, wherein the agent unit communicates with the connection unit by long polling.

7. The information processing system according to claim 3, wherein the agent unit comprises a resource registration unit that transmits resource information of the analysis server to the resource management unit.

8. The information processing system according to claim 3, wherein the agent unit includes a system construction unit that deploys and / or executes the program on the analysis server.

9. An information processing system as described in claim 8, further comprising a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein the data analysis client terminal transmits analysis information relating to the analysis processing of at least one of the light intensity data and the fluorescent label intensity data to the connection unit, wherein the connection unit determines the program that performs the analysis processing and the analysis server that at least one of deploys and executes the program based on at least one of the analysis information, the resource information, and the program information, and transmits information relating to the determined analysis server and the program to the system construction unit, and wherein the system construction unit at least one of deploys and executes the program on the analysis server based on the received information relating to the analysis server and the program.

10. The information processing system of claim 9, wherein the connection unit determines the program that performs the analysis processing and the analysis server that at least one of deploying and executing the program based on at least one of the analysis information, the resource information, the program information, and information regarding the usage fee for the analysis server, and transmits information regarding the determined analysis server and the program to the system construction unit.

11. The information processing system according to claim 2, further comprising a data dividing unit that divides at least one of the light intensity data and the fluorescent label intensity data based on the resource information and transmits each of the data to different analysis servers.

12. The information processing system according to claim 2, further comprising a data analysis client terminal that analyzes at least one of the light intensity data and the fluorescent label intensity data, and wherein the connection unit transmits information about the analysis server that performs at least one of deploying and executing the program to the data analysis client terminal.

13. The information processing system according to claim 12, wherein the data analysis client terminal accepts designation of at least one of the analysis server and the program, and transmits information relating to at least one of the analysis server and the program to the connection unit.

14. A server system including a system construction unit that deploys and / or executes on an analysis server a program that analyzes at least one of light intensity data and fluorescent label intensity data obtained by irradiating a biological sample with light, wherein at least one of the program and the analysis server is determined based on a database that holds information regarding at least one of the program and the analysis server.

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