A genetic testing laboratory information management method and system

Abstract

This application is applicable to the field of data processing technology, and provides a method and system for managing genetic testing laboratory information, which includes: collecting relevant information of genetic testing; associating relevant information, encrypting and uploading it to the blockchain, and providing it for traceability query; building a network security situation model to evaluate the blockchain network. This application can not only provide complete data support for traceability query, but also ensure the confidentiality, privacy and security of genetic testing information.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and in particular, relates to a method and system for managing information in a genetic testing laboratory. Background Art

[0002] At present, genetic testing technology is becoming more and more mature. According to statistics, genetic testing is usually completed in the laboratory. As the demand for genetic testing continues to increase, a large amount of data and important information is constantly generated and recorded.

[0003] Huge amounts of data and information rely on manual filling, statistics, calculations and report preparation, making it difficult to record, track and control the entire flow and processing of samples. When quality problems occur, it is difficult to trace them. In addition, Trojans, viruses and threatening software programs have quietly sneaked into genetic testing laboratories to steal information and spread bad information. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a genetic testing laboratory information management method and system to solve the above technical problems.

[0005] A first aspect of an embodiment of the present application provides a method for managing information of a genetic testing laboratory, comprising:

[0006] Collect relevant information about genetic testing;

[0007] The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, specifically:

[0008] Each gene to be tested is labeled to generate a unique ID;

[0009] The relevant information and ID of each gene to be tested are associated and encrypted to generate the corresponding key L;

[0010] Store the key L and the corresponding ID in the blockchain;

[0011] When performing a traceback query, the key L is searched by ID;

[0012] After the key L is obtained through the query, the key L is decrypted through the decryption algorithm to obtain the relevant information of the gene to be tested, thus realizing the traceability query;

[0013] Construct a cybersecurity situation model to evaluate the blockchain network, including:

[0014] The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including:

[0015] All relevant information is associated, encrypted and uploaded to the blockchain, the load information of each node in the blockchain is monitored in real time, a decision matrix is ​​built based on the node load information, and the load of each node is evaluated based on the decision matrix to achieve dynamic balancing of the load of each node, thereby improving the traceability query response speed.

[0016] Preferably, the load information of each node in the blockchain includes the node CPU, memory, and bandwidth information; the decision matrix M constructed by the load information is as follows:

[0017]

[0018] In the above formula, M is the decision matrix, n is the number of cycles, CUR, MUR and BUR are the utilization of CPU, memory and bandwidth respectively.

[0019] A second aspect of the embodiment of the present application provides a genetic testing laboratory information management system, including:

[0020] A collection module is used to collect relevant information of genetic testing;

[0021] The management module is used to associate relevant information, encrypt and upload it to the blockchain, and provide traceability query. Specifically:

[0022] Each gene to be tested is labeled to generate a unique ID;

[0023] The relevant information and ID of each gene to be tested are associated and encrypted to generate the corresponding key L;

[0024] Store the key L and the corresponding ID in the blockchain;

[0025] When performing a traceback query, the key L is searched by ID;

[0026] After the key L is obtained through the query, the key L is decrypted through the decryption algorithm to obtain the relevant information of the gene to be tested, thus realizing the traceability query;

[0027] The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including:

[0028] Associate all relevant information, encrypt and upload to the blockchain, monitor the load information of each node in the blockchain in real time, build a decision matrix based on the node load information, and evaluate the load of each node based on the decision matrix to achieve dynamic load balancing of each node, thereby improving the traceability query response speed;

[0029] The load information of each node in the blockchain includes the node CPU, memory, and bandwidth information; the decision matrix M constructed based on the load information is as follows:

[0030]

[0031] In the above formula, M is the decision matrix, n is the number of cycles, CUR, MUR and BUR are the utilization of CPU, memory and bandwidth respectively;

[0032] The evaluation module is used to build a network security situation model to evaluate the blockchain network.

[0033] A third aspect of an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0034] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0035] As can be seen from the above, compared with the prior art, the present application has at least the following advantages:

[0036] 1. This application can provide complete data support for traceability query by associating various related information of genetic testing and inspection, so that information such as sample collection information, patient information, sample experiment progress information, reagent information, test results and test reports can be traced back. When quality problems occur, the problem points can be identified in the first time, and the associated data can be encrypted and uploaded to the blockchain, which can ensure the confidentiality, privacy and security of genetic testing and inspection information.

[0037] 2. Since this application conducts a security situation assessment on the blockchain network that stores genetic testing and verification information, it can ensure the security and reliability of genetic testing and verification information.

[0038] 3. Since the present application collects relevant information of genetic testing through QR codes, manual entry can be avoided, which can effectively improve the efficiency and accuracy of information collection.

[0039] 4. Since the case number and encrypted key of the gene to be tested are uploaded to the blockchain, the information can be stored on the chain without exposing any information of the gene to be tested, which can effectively ensure the security and privacy of the information.

[0040] 5. This application constructs a network security situation model by screening out important feature data in the blockchain network, thereby effectively improving the model prediction or evaluation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 It is a flowchart of a method for managing information of a genetic testing laboratory provided in an embodiment of the present application;

[0043] Figure 2 It is a schematic diagram of the structure of the genetic testing laboratory information management system provided in the embodiment of the present application;

[0044] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0046] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0047] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0048] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0049] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0050] In a specific implementation, the electronic devices described in the embodiments of the present application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and / or touch pads). It should also be understood that in some embodiments, the device is not a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., touch screen displays and / or touch pads).

[0051] In the following discussion, an electronic device including a display and a touch-sensitive surface is described. However, it should be understood that the electronic device may include one or more other physical user interface devices such as a physical keyboard, mouse, and / or joystick.

[0052] The electronic device supports various applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk burning application, a spreadsheet application, a game application, a telephone application, a video conferencing application, an email application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital camcorder application, a web browsing application, a digital music player application, and / or a digital video player application.

[0053] Various applications that can be executed on an electronic device can use at least one common physical user interface device such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and corresponding information displayed on the electronic device can be adjusted and / or changed between applications and / or within corresponding applications. In this way, a common physical architecture of an electronic device (e.g., a touch-sensitive surface) can support a variety of applications with user interfaces that are intuitive and transparent to the user.

[0054] It should be understood that the size of the serial numbers of the steps in this embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0055] In order to illustrate the technical solution described in this application, a specific embodiment is provided below for illustration.

[0056] See also Figure 1 , Figure 1 : is a flow chart of the genetic testing laboratory information management method provided in the embodiment of the present application, such as Figure 1 As shown, a method for managing information in a genetic testing laboratory includes the following contents:

[0057] Collect relevant information about genetic testing;

[0058] Associate all relevant information, encrypt and upload to the blockchain for traceability query;

[0059] Build a cybersecurity situation model to assess blockchain networks.

[0060] Obviously, by associating all relevant information of genetic testing and inspection, complete data support can be provided for traceability queries, so that sample collection information, patient information, sample experiment progress information, reagent usage information, test results and test reports can be traced back. When quality problems occur, the problem points can be identified in the first time, and the associated data can be encrypted and uploaded to the blockchain to ensure the confidentiality, privacy and security of genetic testing and inspection information.

[0061] At the same time, since the blockchain network that stores genetic testing and verification information is subject to security situation assessment, the security and reliability of genetic testing and verification information can be ensured.

[0062] In some embodiments, the collection of relevant information for genetic testing includes the following:

[0063] Collect relevant information of genetic testing through QR code.

[0064] Since relevant information of genetic testing is collected through QR codes and manual entry is avoided, the efficiency and accuracy of information collection can be effectively improved.

[0065] In this embodiment, the relevant information data of genetic testing and inspection include genetic testing application form data, sample collection data, sample quality inspection data, library quality inspection data, sequencing machine data, sequencing data quality indicator data, test result record data, test report data and abnormal situation data.

[0066] In some embodiments, the relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including the following:

[0067] Generate a unique identification code for the gene to be tested, which will serve as its exclusive case number;

[0068] Performing association and encryption calculation for each relevant information corresponding to each gene to be tested, so as to obtain a key belonging to the gene to be tested;

[0069] After associating the relevant information corresponding to each gene to be tested, the correlation of the relevant information can also be calculated;

[0070] The calculation formula of the correlation is:

[0071]

[0072] Among them, K is the relevance, D1 is the total number of words in any data in the relevant information, Y1 is the mean of all data in the relevant information, X1 is the total number of words in any data in similar information, C1 is the mean of all data in similar information, j is the number of retrievals of the number of words in the data, t1 is the mean of the retrieval time, and t2 is the total retrieval time;

[0073] The similar information is obtained by searching all information through big data technology and extracting keywords from all information, wherein at least two groups of data whose keyword repetition rate reaches 1 / 3 of the total number of words in all information are set as similar information; the relevant information is sorted from large to small according to the size of the relevance to facilitate subsequent tracing.

[0074] Upload the case number and key to the blockchain.

[0075] Obviously, by uploading the case number and encrypted key of the gene to be tested to the blockchain, the information can be stored on the chain without exposing any information of the gene to be tested, which can effectively ensure the security and privacy of the information. In the tracing process, tracing from the most relevant relevant information can greatly improve the efficiency of tracing, save the time of tracing, and enhance the accuracy of tracing. By calculating the correlation between relevant information and similar information, the accuracy of correlation calculation is greatly enhanced.

[0076] In this embodiment, the relevant information is associated, encrypted and uploaded to the blockchain for traceability query, and may also include the following:

[0077] Query the key corresponding to the gene to be tested according to the case number of the gene to be tested;

[0078] The encrypted information about the gene to be tested is decrypted according to the key to provide traceability query.

[0079] Specifically, all relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including the following:

[0080] Each gene to be tested is labeled to generate a unique ID;

[0081] The relevant information and ID of each gene to be tested are associated and encrypted to generate the corresponding key L;

[0082] Store the key L and the corresponding ID in the blockchain;

[0083] When performing a traceback query, the key L is searched by ID;

[0084] After the key L is obtained through the query, the key L is decrypted through the decryption algorithm to obtain the relevant information of the gene to be tested, thereby realizing the traceability query.

[0085] Obviously, the above solution can ensure the privacy and integrity of genetic testing information; at the same time, based on the characteristics of blockchain distributed storage, it can effectively reduce information storage pressure and save costs.

[0086] In some embodiments, the relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including the following:

[0087] Associate all relevant information, encrypt and upload to the blockchain, monitor the load information of each node in the blockchain in real time, build a decision matrix based on the node load information, and evaluate the load of each node based on the decision matrix to achieve dynamic load balancing of each node, thereby improving the traceability query response speed;

[0088] The load information of each node in the blockchain includes information such as node CPU, memory, and bandwidth. The decision matrix M constructed based on the load information is as follows:

[0089]

[0090] In the above formula, M is the decision matrix, n is the number of cycles, CUR, MUR and BUR are the utilization of CPU, memory and bandwidth respectively;

[0091] Obviously, due to the distributed storage characteristics of blockchain, and the heterogeneity of node resources in the distributed storage environment, in order to reduce the transmission of data between nodes during the data analysis and calculation process and make full use of node computing resources, dynamic adjustment through load balancing can improve the response speed of traceability queries.

[0092] In some embodiments, a network security situation model is constructed to evaluate the blockchain network, including the following:

[0093] Filter out important feature data in the blockchain network, build a network security situation model based on the important feature data, and evaluate the blockchain network.

[0094] Obviously, the network security situation model constructed by screening out important feature data in the blockchain network can effectively improve the model prediction or evaluation accuracy.

[0095] In this embodiment, important characteristic data in the blockchain network is screened out, and a network security situation model is constructed based on the important characteristic data to evaluate the blockchain network. The important characteristic data in the blockchain network is screened out, including the following contents:

[0096] Use the feature data from all current blockchain networks to train and obtain the verification model;

[0097] Verify the model effect through the validation set and then calculate the loss loss raw ;

[0098] Shuffle the data corresponding to a feature f of the validation set, predict again and get the loss loss f ;

[0099] Difference of the above scores can be used to get the importance of feature f for prediction imp f =|loss f -loss raw |;

[0100] Execute the above method on each feature data in the blockchain network in turn to obtain the importance of each feature for prediction;

[0101] According to the calculated importance, important feature data in the blockchain network is screened out.

[0102] Obviously, the above-mentioned important feature data screening scheme is carried out after the model training is completed, and there is no need to train other models, so it can effectively save time.

[0103] At the same time, the above scheme can obtain a numerical measure of the importance of each feature to the model. Therefore, it is possible to intuitively understand which feature is important and why it is important, which is very helpful in improving the accuracy of the model evaluation results.

[0104] In this embodiment, a network security situation model is constructed to evaluate the blockchain network, including the following contents:

[0105] Capture network data and preprocess it to obtain data items and indicator values;

[0106] Evaluate data items and indicator values ​​through support vector machine classification;

[0107] The evaluation results of the blockchain network are calculated and output based on the evaluation results and weight strategy.

[0108] Among them, in order to make the data items and index values ​​meet the parameter requirements of the support vector machine, the data is normalized in a unified way so that its range is within the range of [0,1]. The normalization formulas for data items and index values ​​are as follows:

[0109]

[0110] In the above formula, F(i) is the normalized index value; D i is the current indicator value.

[0111] Specifically, the security situation level is divided into categories, where a security index between 0.0–0.2 is considered relatively safe; 0.2–0.5 is considered slightly dangerous; 0.5–0.8 is considered moderately dangerous; and 0.8–1.0 is considered highly dangerous.

[0112] Based on the same inventive concept, the genetic testing laboratory information management system provided in the embodiment of the present application is as follows: Figure 2 As shown, including:

[0113] Collection module 21, used to collect relevant information of gene detection and testing;

[0114] Management module 22, used to associate relevant information, encrypt and upload it to the blockchain, and provide traceability query;

[0115] The evaluation module 23 is used to build a network security situation model to evaluate the blockchain network.

[0116] Obviously, by associating all relevant information of genetic testing and inspection, complete data support can be provided for traceability queries, so that sample collection information, patient information, sample experiment progress information, reagent usage information, test results and test reports can be traced back. When quality problems occur, the problem points can be identified in the first time, and the associated data can be encrypted and uploaded to the blockchain to ensure the confidentiality, privacy and security of genetic testing and inspection information.

[0117] At the same time, since the blockchain network that stores genetic testing and verification information is subject to security situation assessment, the security and reliability of genetic testing and verification information can be ensured.

[0118] Figure 3 is a structural diagram of an electronic device provided in an embodiment of the present application. As shown in the figure, the electronic device 4 of the embodiment includes: at least one processor 40 ( Figure 3 Only one is shown in the figure), a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, wherein the processor 40 implements the steps of any of the above-mentioned method embodiments when executing the computer program 42.

[0119] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 3 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0120] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0121] The memory 41 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. The memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the electronic device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 41 is used to store the computer program and other programs and data required by the electronic device. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0122] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0123] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0124] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0128] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0129] The present application implements all or part of the processes in the above-mentioned embodiment method, and may also be implemented through a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0130] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for managing information in a genetic testing laboratory, characterized in that: include: Collect relevant information about genetic testing; All relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including: Each gene to be tested is labeled to generate a unique ID; The relevant information and ID of each gene to be tested are associated and encrypted to generate the corresponding key L; Store the key L and the corresponding ID in the blockchain; When performing a traceback query, the key L is searched by ID; After the key L is obtained through the query, the key L is decrypted through the decryption algorithm to obtain the relevant information of the gene to be tested, thus realizing the traceability query; Construct a cybersecurity situation model to evaluate the blockchain network, including: The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including: Associate all relevant information, encrypt and upload to the blockchain, monitor the load information of each node in the blockchain in real time, build a decision matrix based on the node load information, and evaluate the load of each node based on the decision matrix to achieve dynamic load balancing of each node, thereby improving the traceability query response speed; The construction of a network security situation model to evaluate the blockchain network includes: Filter out important characteristic data in the blockchain network, and build a network security situation model based on the important characteristic data to evaluate the blockchain network; Among them, the important characteristic data in the blockchain network are screened out, including: Use the feature data from all current blockchain networks to train and obtain the verification model; Verify the model effect through the validation set and then calculate the loss loss raw ; Shuffle the data corresponding to a feature f of the validation set, predict again and get the loss loss f ; Difference of the above loss is obtained to get the importance of feature f for prediction imp f =|loss f -loss raw |; Perform the above steps on each feature data in the blockchain network in turn to obtain the importance of each feature for prediction; According to the calculated importance, important feature data in the blockchain network is screened out.

2. The method according to claim 1, characterized in that: The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including: Generate a unique identification code for the gene to be tested, which will serve as its exclusive case number; Performing association and encryption calculation for each relevant information corresponding to each gene to be tested, so as to obtain a key belonging to the gene to be tested; Upload the case number and key to the blockchain.

3. The method according to claim 2, characterized in that: Also includes: Query the key corresponding to the gene to be tested according to the case number of the gene to be tested; The encrypted information about the gene to be tested is decrypted according to the key to provide traceability query.

4. The method according to claim 1, characterized in that: The network security situation model is constructed to evaluate the blockchain network, including: Capture network data and preprocess it to obtain data items and indicator values; Evaluate data items and indicator values ​​through support vector machine classification; The evaluation results of the blockchain network are calculated and output based on the evaluation results and weight strategy.

5. The method according to claim 4, characterized in that: Also includes: The data items and indicator values ​​are normalized in a unified way so that their range is within the range of [0,1]. The normalization formulas for data items and indicator values ​​are as follows: In the above formula, F(i) is the normalized index value; D i is the current indicator value.

6. The method according to claim 1, characterized in that: The load information of each node in the blockchain includes the node CPU, memory, and bandwidth information; the decision matrix M constructed based on the load information is as follows: In the above formula, M is the decision matrix, n is the number of cycles, CUR, MUR and BUR are the utilization of CPU, memory and bandwidth respectively.

7. The method according to claim 6, characterized in that: in, All relevant information data of genetic testing and inspection include: genetic testing application form data, sample collection data, sample quality inspection data, library quality inspection data, sequencing machine data, sequencing data quality indicator data, test result record data, test report data and abnormal situation data.

8. A genetic testing laboratory information management system, characterized in that: include: A collection module is used to collect relevant information of genetic testing; The management module is used to associate relevant information, encrypt and upload it to the blockchain, and provide traceability query. Specifically: Each gene to be tested is labeled to generate a unique ID; The relevant information and ID of each gene to be tested are associated and encrypted to generate the corresponding key L; Store the key L and the corresponding ID in the blockchain; When performing a traceback query, the key L is searched by ID; After the key L is obtained through the query, the key L is decrypted through the decryption algorithm to obtain the relevant information of the gene to be tested, thus realizing the traceability query; The relevant information is associated, encrypted and uploaded to the blockchain for traceability query, including: Associate all relevant information, encrypt and upload to the blockchain, monitor the load information of each node in the blockchain in real time, build a decision matrix based on the node load information, and evaluate the load of each node based on the decision matrix to achieve dynamic load balancing of each node, thereby improving the traceability query response speed; An assessment module, which is used to build a network security situation model to assess the blockchain network; The construction of a network security situation model to evaluate the blockchain network includes: Filter out important characteristic data in the blockchain network, and build a network security situation model based on the important characteristic data to evaluate the blockchain network; Among them, the important characteristic data in the blockchain network are screened out, including: Use the feature data from all current blockchain networks to train and obtain the verification model; Verify the model effect through the validation set and then calculate the loss loss raw ; Shuffle the data corresponding to a feature f of the validation set, predict again and get the loss loss f ; Difference of the above loss is obtained to get the importance of feature f for prediction imp f =|loss f -loss raw |; Perform the above steps on each feature data in the blockchain network in turn to obtain the importance of each feature for prediction; According to the calculated importance, important feature data in the blockchain network is screened out.

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