Cryoelectron microscope density map database building method and system, storage medium and equipment
By acquiring high-resolution density map data from EMDB, performing two-dimensional particle processing and three-dimensional reconstruction, generating low-resolution density maps consistent with experimental data and setting high-quality labels, the problems of insufficient data volume and inconsistent noise distribution in existing technologies are solved, improving the quantity and quality of low-resolution density maps and enhancing the training effect of artificial intelligence models.
Patent Information
- Application Number
- CN202510950461.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-10
- Publication Date
- 2025-11-25
AI Technical Summary
Existing techniques for generating low-resolution cryo-electron microscopy density map datasets suffer from insufficient data volume, low label quality, and noise distribution that does not match experimental data, which affects the training effect of artificial intelligence models.
By acquiring high-resolution density map data from EMDB, two-dimensional particle data is obtained using a preset data processing workflow and three-dimensional reconstruction is performed. The high-resolution density map is then compared and verified, and random sampling is performed to generate a low-resolution density map with the same noise distribution as the experimental data. The PDB model corresponding to the high-resolution density map is used as the label.
This significantly increased the quantity and quality of low-resolution density maps, ensuring that the noise distribution was consistent with the experimental data, improving the accuracy of the labels, and enhancing the training effect of the artificial intelligence model.
Smart Images
Figure CN121009201A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of cryo-electron microscopy data processing technology, and in particular relates to a method, system, storage medium and device for building a cryo-electron microscopy density map database. Background Technology
[0002] With the widespread application of artificial intelligence (AI) computational methods in cryo-electron microscopy (cryo-EM) data analysis, large-scale, high-quality data is crucial for developing effective AI methods. Currently, AI model training for low-resolution density maps (ranging from 4 to 10 angstroms) primarily relies on the following three strategies to obtain labeled cryo-EM density map datasets: 1. Directly use the density map from the EMDB database and use the corresponding PDB model as the label.
[0003] Second, after performing low-frequency filtering on the high-resolution density map of EMDB (resolution range of 0 to 4 angstroms), a low-resolution density map is obtained, and then the PDB model corresponding to the high-resolution density map is used as the label.
[0004] 3. Generate simulated density maps from the PDB model using software such as ChimeraX, and use the input PDB model as labels.
[0005] The main solutions currently in use still have some problems, such as insufficient data volume, noise distribution not matching experimental data, and low label quality.
[0006] The first scheme described above, while having the same noise distribution as the experimental data, suffers from insufficient data volume and low label quality. Currently, the EMDB database only has 18,883 high-resolution density maps (0-4 Å resolution) with corresponding PDB models, while the number of PDB models corresponding to low-resolution density maps (4-10 Å) is even smaller (only 4,438). This lack of data severely limits the training effect of artificial intelligence models. Furthermore, low-resolution density maps struggle to clearly present detailed features (such as amino acid side chains), resulting in poor accuracy of the atomic models (i.e., labels) built upon them, thus affecting the performance of the trained artificial intelligence models.
[0007] The aforementioned Schemes 2 and 3, because they can generate different results at different resolutions, can generate massive amounts of data in batches. They also use high-resolution atomic models to ensure high-quality labels. However, both suffer from noise distribution discrepancies with experimental data. Scheme 2 produces a high overall signal-to-noise ratio (SNR) for its high-resolution density map (including low-frequency components), but the SNR of real low-resolution data is typically very low, leading to a discrepancy between the noise distribution of the low-resolution density map obtained through low-frequency filtering and the actual experimental data. Scheme 3 generates a low-resolution density map that contains only simple Gaussian noise, and its noise distribution differs significantly from the real data. Therefore, the noise distribution of the low-resolution density maps generated by Schemes 2 and 3 differs greatly from the real data. If used to train artificial intelligence methods, this can lead to a decline in the performance of the trained models on real data. Summary of the Invention
[0008] To address the shortcomings of existing technologies, this application provides a method, system, storage medium, and device for constructing a cryo-electron microscopy density map database. By sampling two-dimensional particles, low-resolution density maps are generated, enabling the generation of large batches of new data with noise distributions identical to experimental data. Furthermore, high-quality PDB models corresponding to the original high-resolution EMDB density maps can be used as labels, thereby improving the quantity and quality of low-resolution density maps.
[0009] This application is achieved through the following technical solution: Obtain high-resolution density map data from EMDB, acquire corresponding electron microscope images based on the high-resolution density map, and obtain two-dimensional particle data and reconstructed density map through a preset data processing flow. The reproduced density map is compared and verified based on the high-resolution density map. A sampling task and a reconstruction task are established to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. A preset number of random numbers are generated according to preset rules and set as parameters for the sampling task. The sampling task and reconstruction task are run repeatedly. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
[0010] Optional, The process of acquiring high-resolution density map data from the EMDB, obtaining corresponding electron micrographs based on the high-resolution density maps, and acquiring two-dimensional particle data and reconstructed density maps through a preset data processing flow includes: Retrieve the corresponding electron microscope image based on the high-resolution density map; Based on the high-resolution density map and the corresponding electron microscope image, two-dimensional particle data are obtained; Based on the high-resolution density map and two-dimensional particle data, a three-dimensional reconstruction is performed to obtain a reproduced density map.
[0011] Optional, The comparison and verification of the reproduced density map based on the high-resolution density map includes: The three-dimensional starting coordinates of the high-resolution density map are copied to the reproduced density map and compared with the high-resolution density map to determine whether they completely overlap. If they do not completely overlap, then reacquire the two-dimensional particle data and reproduce the density map; If they completely overlap, the verification is considered successful.
[0012] Optional, The establishment of the sampling and reconstruction tasks involves randomly sampling the two-dimensional particle data and performing three-dimensional reconstruction using a high-resolution density map, including: A sampling task is established to randomly sample the two-dimensional particle data to obtain a subset of the two-dimensional particle data. A reconstruction task is established to perform three-dimensional reconstruction based on the two-dimensional particle data subset and the high-resolution density map, thereby obtaining a low-resolution density map.
[0013] Optional, The process involves generating a preset number of random numbers according to preset rules, setting them as parameters for the sampling task, repeatedly running the sampling and reconstruction tasks, and storing the resulting low-resolution density map in a database if it meets a preset resolution threshold. Generate a random number between a preset value and the preset number of two-dimensional particles contained in the two-dimensional particle data; A sampling and reconstruction task is performed based on each random number to obtain a low-resolution density map. Determine whether the low-resolution density map meets the preset resolution threshold. If it does, store it in the database and set a label.
[0014] Optional, The method further includes: The three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
[0015] This application also provides a cryo-electron microscopy density map database construction system for implementing the aforementioned method, the system comprising: The comparison and verification module is used to compare and verify the reproducible density map based on the high-resolution density map. The sampling and reconstruction module is used to establish sampling and reconstruction tasks, and to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. The density map generation module is used to generate a preset number of random numbers according to preset rules, set them as parameters of the sampling task, and repeatedly run the sampling task and reconstruction task. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
[0016] Optional, The system is also configured to: The three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
[0017] This application also provides a computer-readable storage medium storing one or more programs, which, when executed, can implement the aforementioned method for building a cryo-electron microscopy density map database.
[0018] This application also provides a device, including a processor, a communication interface, a computer-readable storage medium, and a communication bus; wherein the processor, the communication interface, and the computer-readable storage medium communicate with each other through the communication bus; The processor is used to execute programs stored in a computer-readable storage medium.
[0019] Compared with the prior art, this application has the following advantages: 1. The cryo-electron microscopy density map database construction method proposed in this application obtains electron microscope images based on high-resolution density maps in the EMDB database, processes them to obtain two-dimensional particle data, and generates low-resolution density maps by sampling two-dimensional particles. This method can obtain a large amount of new data with noise distribution that is exactly the same as the experimental data, thereby improving the quantity and quality of low-resolution density maps.
[0020] 2. By verifying whether the high-resolution density map is consistent with the reproduced density map, it is possible to determine whether there are any problems in the processing of the original data, ensure that the noise distribution of the generated low-resolution density map is exactly the same as that of the experimental data, and use the corresponding high-quality PDB model as a label to improve the quality of the generated low-resolution density map.
[0021] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description
[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0023] Figure 1 A flowchart illustrating the method for building a cryo-electron microscopy density map database is shown. Figure 2 A schematic block diagram of the cryo-electron microscopy density map database construction system is shown. Figure 3 This is a schematic diagram of the structure of a device according to an embodiment of this application. Detailed Implementation
[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0025] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.
[0026] See appendix Figure 1 The method of this application includes: S1. Obtain high-resolution density map data from EMDB, obtain corresponding electron microscope images based on the high-resolution density map, and obtain two-dimensional particle data and reproducible density map through a preset data processing flow. Among them, the corresponding electron microscope image is retrieved based on the high-resolution density map; Based on the high-resolution density map and the corresponding electron microscope image, two-dimensional particle data are obtained; Based on the high-resolution density map and two-dimensional particle data, a three-dimensional reconstruction is performed to obtain a reproduced density map.
[0027] S2. Compare and verify the reproduced density map based on the high-resolution density map; Specifically, the three-dimensional starting coordinates of the high-resolution density map are copied to the reproduced density map and compared with the high-resolution density map to determine whether they completely overlap. If they do not completely overlap, then reacquire the two-dimensional particle data and reproduce the density map; If they completely overlap, the verification is considered successful.
[0028] S3. Establish sampling and reconstruction tasks to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map; Among them, a sampling task is established to randomly sample the two-dimensional particle data to obtain a subset of the two-dimensional particle data. A reconstruction task is established to perform three-dimensional reconstruction based on the two-dimensional particle data subset and the high-resolution density map, thereby obtaining a low-resolution density map.
[0029] S4. Generate a preset number of random numbers according to preset rules, set them as parameters of the sampling task, and repeatedly run the sampling task and reconstruction task. If the obtained low-resolution density map meets the preset resolution threshold, store it in the database and set a label.
[0030] Among them, a random number is generated between a preset value and the preset number of two-dimensional particles contained in the two-dimensional particle data; A sampling and reconstruction task is performed based on each random number to obtain a low-resolution density map. Determine whether the low-resolution density map meets the preset resolution threshold. If it does, store it in the database and set a label. Specifically, the three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
[0031] Specifically, The embodiments of this application provide a method for building a database of low-resolution cryo-electron microscopy density maps with high-quality labels. This method can increase the number of low-resolution density maps in the database to more than a thousand times that of currently available similar data. At the same time, each low-resolution density map is accompanied by a high-quality atomic model as a label.
[0032] I. Data preparation and data processing.
[0033] Retrieve high-resolution density map data from the EMDB, obtain corresponding electron micrographs based on the high-resolution density maps, and acquire two-dimensional particle data and reconstructed density maps through a preset data processing workflow, including: Retrieve the corresponding electron microscope image based on the high-resolution density map; Based on the high-resolution density map and the corresponding electron microscope image, two-dimensional particle data are obtained; Based on the high-resolution density map and two-dimensional particle data, a three-dimensional reconstruction is performed to obtain a reproduced density map.
[0034] In this embodiment, high-resolution density map data (resolution range of 0 to 4 angstroms) is obtained from the EMDB. Based on the obtained high-resolution density maps, electron microscope images associated with each high-resolution density map can be searched and downloaded from the EMPIAR database. Then, the literature data corresponding to the EMDB entry for that high-resolution density map is read, and the electron microscope images corresponding to the high-resolution density map are retrieved from the downloaded electron microscope images according to the method descriptions and flowcharts in the literature. Using cryoSPARC, a preset data processing flow is applied to the high-resolution density map and the corresponding electron microscope images to obtain a set of two-dimensional particle data corresponding to the high-resolution density map and a new high-resolution density map (called the "reproduced density map"). The data processing flow mainly includes motion correction, phase difference function estimation, particle selection, two-dimensional classification, three-dimensional classification, and three-dimensional reconstruction. The data flow is not fixed and can be set as needed, but the last step must be three-dimensional reconstruction, that is, inputting a set of two-dimensional particle data and an initial density map, and outputting a reproduced density map. Use the EMDB high-resolution density map as the initial density map for 3D reconstruction. Specifically, create a new "Import 3D Volumes" task to import the EMDB high-resolution density map, and use this task as the "Initial volume" parameter of the 3D reconstruction task.
[0035] II. Comparison and verification.
[0036] The reproducible density map is compared and verified based on the high-resolution density map, including: The three-dimensional starting coordinates of the high-resolution density map are copied to the reproduced density map and compared with the high-resolution density map to determine whether they completely overlap. If they do not completely overlap, then reacquire the two-dimensional particle data and reproduce the density map; If they completely overlap, the verification is considered successful.
[0037] In this embodiment, the three-dimensional starting coordinates nxstart, nystart, and nzstart (representing the offset between the density map and the corresponding atomic model) stored in the high-resolution density map are copied to the reproduced density map to ensure that the reproduced density map is spatially aligned with the high-resolution density map. Then, the high-resolution density map and the reproduced density map are opened in ChimeraX to determine whether the biomolecular structures contained in them completely overlap. If they do not completely overlap, the steps of obtaining two-dimensional particle data and the reproduced density map through the preset data processing flow are repeated.
[0038] By verifying whether the high-resolution density map is consistent with the reproduced density map, we can determine whether there are any problems with the processing of the original data and ensure the correct mapping of subsequent labels.
[0039] III. Establish data sampling and reconstruction tasks.
[0040] Establish sampling and reconstruction tasks to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map, including: A sampling task is established to randomly sample the two-dimensional particle data to obtain a subset of the two-dimensional particle data. A reconstruction task is established to perform three-dimensional reconstruction based on the two-dimensional particle data subset and the high-resolution density map, thereby obtaining a low-resolution density map.
[0041] In this embodiment, a new task of type "Particle Sets Tool" is created in the cryoSPARC browser interface, called the "Sampling Task," to randomly sample two-dimensional particle data and obtain a subset of two-dimensional particle data. A "Reconstruction Task" is created to perform three-dimensional reconstruction based on the sampled subset of two-dimensional particle data and the high-resolution density map. The "Particle stacks" parameter of the reconstruction task is set to the two-dimensional particle subset output by the sampling task, and the "Initial volume" parameter is set to the "Import 3D Volumes" task created during the data processing. Running the reconstruction task will then yield a low-resolution density map.
[0042] 4. Repeat the sampling and reconstruction task to generate a low-resolution density map.
[0043] A preset number of random numbers are generated according to preset rules and set as parameters for the sampling task. The sampling and reconstruction tasks are run repeatedly. If the obtained low-resolution density map meets a preset resolution threshold, it is stored in the database and labeled, including: Generate a random number between a preset value and the preset number of two-dimensional particles contained in the two-dimensional particle data; A sampling and reconstruction task is performed based on each random number to obtain a low-resolution density map. Determine whether the low-resolution density map meets the preset resolution threshold. If it does, store it in the database and set a label.
[0044] Specifically, the three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
[0045] In this embodiment, the Python command-line interface provided by cryoSPARC is used to repeatedly perform the following operations: generate 3000 random numbers between 100 and the number of two-dimensional particles contained in the two-dimensional particle data, set them as parameters for the sampling task, perform the sampling task and reconstruction task based on each random number, and save the resulting density map resolution to the database if it is between 4 and 10 angstroms (copy the three-dimensional starting coordinates of the EMDB high-resolution density map to the low-resolution density map, and use the PDB model corresponding to the EMDB high-resolution density map as the label of the generated low-resolution density map).
[0046] In this embodiment, 1850 EMDB density maps with a resolution between 0 and 4 angstroms and possessing a PDB model were obtained, and electron microscope images could be found in EMPIAR. Using the method of this embodiment, 3000 low-resolution density maps can be generated for each EMDB density map that meets the conditions, ultimately constructing a database containing approximately five million low-resolution density maps.
[0047] See appendix Figure 2 The structure of a cryo-electron microscopy density map database construction system for implementing the above method is shown, including a data preparation module, a comparison and verification module, a sampling and reconstruction module, and a density map generation module.
[0048] The data preparation module is used to acquire high-resolution density map data in EMDB, obtain corresponding electron microscope images based on the high-resolution density map, and acquire two-dimensional particle data and reproducible density maps through a preset data processing flow. The comparison and verification module is used to compare and verify the reproducible density map based on the high-resolution density map. The sampling and reconstruction module is used to establish sampling and reconstruction tasks, and to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. The density map generation module is used to generate a preset number of random numbers according to preset rules, set them as parameters of the sampling task, and repeatedly run the sampling task and reconstruction task. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
[0049] Furthermore, this application also provides a cryo-electron microscopy density map database construction device, including: The data preparation module acquires high-resolution density map data from the EMDB, obtains corresponding electron microscope images based on the high-resolution density map, and acquires two-dimensional particle data and reproducible density maps through a preset data processing flow. The comparison and verification module performs comparison and verification on the reproduced density map based on the high-resolution density map. The sampling and reconstruction module establishes sampling and reconstruction tasks to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. The density map generation module generates a preset number of random numbers according to preset rules, sets them as parameters for the sampling task, and repeatedly runs the sampling task and reconstruction task. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
[0050] Based on the same concept, this application also provides a computer-readable storage medium storing one or more programs, which, when executed, can realize the aforementioned method for building a cryo-electron microscopy density map database.
[0051] like Figure 3 As shown in the illustration, this application also provides a device including a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus.
[0052] The memory is a computer-readable storage medium used to store one or more programs.
[0053] The processor is configured to execute a program stored in a computer-readable storage medium.
[0054] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus.
[0055] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A method for constructing a cryo-electron microscopy density map database, characterized in that, include: Obtain high-resolution density map data from EMDB, acquire corresponding electron microscope images based on the high-resolution density map, and obtain two-dimensional particle data and reconstructed density map through a preset data processing flow. The reproduced density map is compared and verified based on the high-resolution density map. A sampling task and a reconstruction task are established to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. A preset number of random numbers are generated according to preset rules and set as parameters for the sampling task. The sampling task and reconstruction task are run repeatedly. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
2. The method according to claim 1, characterized in that, The process of acquiring high-resolution density map data from the EMDB, obtaining corresponding electron micrographs based on the high-resolution density maps, and acquiring two-dimensional particle data and reconstructed density maps through a preset data processing flow includes: Retrieve the corresponding electron microscope image based on the high-resolution density map; Based on the high-resolution density map and the corresponding electron microscope image, two-dimensional particle data are obtained; Based on the high-resolution density map and two-dimensional particle data, a three-dimensional reconstruction is performed to obtain a reproduced density map.
3. The method according to claim 1, characterized in that, The comparison and verification of the reproduced density map based on the high-resolution density map includes: The three-dimensional starting coordinates of the high-resolution density map are copied to the reproduced density map and compared with the high-resolution density map to determine whether they completely overlap. If they do not completely overlap, then reacquire the two-dimensional particle data and reproduce the density map; If they completely overlap, the verification is considered successful.
4. The method according to claim 1, characterized in that, The establishment of the sampling and reconstruction tasks involves randomly sampling the two-dimensional particle data and performing three-dimensional reconstruction using a high-resolution density map, including: A sampling task is established to randomly sample the two-dimensional particle data to obtain a subset of the two-dimensional particle data. A reconstruction task is established to perform three-dimensional reconstruction based on the subset of two-dimensional particle data and the high-resolution density map, thereby obtaining a low-resolution density map.
5. The method according to claim 1, characterized in that, The process involves generating a preset number of random numbers according to preset rules, setting them as parameters for the sampling task, repeatedly running the sampling and reconstruction tasks, and storing the resulting low-resolution density map in a database if it meets a preset resolution threshold. Generate a random number between a preset value and the preset number of two-dimensional particles contained in the two-dimensional particle data; A sampling and reconstruction task is performed based on each random number to obtain a low-resolution density map. Determine whether the low-resolution density map meets the preset resolution threshold. If it does, store it in the database and set a label.
6. The method according to any one of claims 1-5, characterized in that, The method further includes: The three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
7. A cryo-electron microscopy density map database construction system, characterized in that, The system includes: The data preparation module is used to acquire high-resolution density map data in EMDB, obtain corresponding electron microscope images based on the high-resolution density map, and acquire two-dimensional particle data and reproducible density maps through a preset data processing flow. The comparison and verification module is used to compare and verify the reproducible density map based on the high-resolution density map. The sampling and reconstruction module is used to establish sampling and reconstruction tasks, and to randomly sample the two-dimensional particle data and perform three-dimensional reconstruction by combining it with a high-resolution density map. The density map generation module is used to generate a preset number of random numbers according to preset rules, set them as parameters of the sampling task, and repeatedly run the sampling task and reconstruction task. If the obtained low-resolution density map meets the preset resolution threshold, it is stored in the database and a label is set.
8. The system according to claim 7, characterized in that, The system is also configured to: The three-dimensional starting coordinates of the high-resolution density map are copied to the low-resolution density map stored in the database; The PDB model corresponding to the high-resolution density map is mapped to the low-resolution density map and used as the label of the low-resolution density map.
9. A computer-readable storage medium storing one or more programs, characterized in that, When one or more of these programs are executed, the method for building a cryo-electron microscopy density map database as described in any one of claims 1-6 can be implemented.
10. An electronic device, comprising a processor, a communication interface, a computer-readable storage medium as described in claim 9, and a communication bus; wherein, The processor, communication interface, and computer-readable storage medium communicate electronically with each other via a communication bus; characterized in that, The processor is used to execute programs stored in a computer-readable storage medium.