CN114388055B - Protein section generation method based on brain infrared control - Google Patents
Protein section generation method based on brain infrared control Download PDFInfo
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- G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
- G16B15/20—Protein or domain folding
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Abstract
The invention discloses a protein section generation method, a device, equipment and a computer readable storage medium based on brain infrared control, wherein the protein section generation method based on brain infrared control comprises the following steps: establishing a three-dimensional space in a terminal, and loading a three-dimensional image of a protein to be observed in the three-dimensional space; mapping the three-dimensional space to a display module connected with the terminal in real time; establishing a reference plane in the three-dimensional space; collecting brain infrared signals of a user in real time, and adjusting the reference surface according to the brain infrared signals; and after receiving the confirmation instruction, generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference. The method has the advantages of convenience in operation and wide applicability.
Description
Technical Field
The invention relates to the technical field of protein section generation, in particular to a protein section generation method, device and equipment based on brain infrared control and a computer readable storage medium.
Background
The spatial structure body of protein formed by stacking polypeptide chains in a spatially disordered manner is widely used in the computer three-dimensional imaging technology of protein in order to understand the microstructure thereof.
However, attention is paid to the arrangement of basic amino acid functional units, and there is no clear knowledge of the dense distribution of the protein interior and the porosity.
In order to intuitively show the conditions of dense distribution, porosity and the like in the protein, it is common practice to perform a boolean subtraction operation on the protein with a virtual plane on a computer, so as to obtain a corresponding sectional view. The cross section operation needs to select a plurality of references and set a plurality of parameters, so that the operation is complex, and the professional ability of a user is high.
Disclosure of Invention
The embodiment of the application aims to simplify the section generation mode of the protein by providing the protein section generation method based on brain infrared control.
In order to achieve the above object, an embodiment of the present application provides a method for generating a protein cross section based on brain infrared control, including:
establishing a three-dimensional space in a terminal, and loading a three-dimensional image of a protein to be observed in the three-dimensional space;
mapping the three-dimensional space to a display module connected with the terminal in real time;
establishing a reference plane in the three-dimensional space;
collecting brain infrared signals of a user in real time, and adjusting the reference surface according to the brain infrared signals;
and after receiving the confirmation instruction, generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference.
In an embodiment, adjusting the reference plane according to the brain infrared signal includes:
identifying the type of the current brain infrared signal according to the pre-trained digital classification model;
confirming a preset adjustment instruction corresponding to the current brain infrared signal;
and adjusting the reference surface based on the preset adjustment instruction.
In an embodiment, before collecting the brain infrared signals of the user, the method further comprises:
establishing a corresponding table of the adjusting instruction and the digital visual object;
displaying the digital visual object in the corresponding table of the adjusting instruction and the digital visual object to a user;
collecting brain infrared signals when a user observes the digital visual object, and pre-classifying the collected brain infrared signals to establish a historical brain infrared database of the user;
establishing a digital classification model for classifying the brain infrared signals;
and training the digital classification model based on a historical brain infrared database of the user until the training of the digital classification model is completed.
In one embodiment, before pre-classifying the acquired brain infrared signals, the method further comprises:
and carrying out noise reduction treatment on the acquired brain infrared signals.
In an embodiment, establishing a reference plane in the three-dimensional space includes:
acquiring the geometric center of the three-dimensional image of the protein to be observed;
and establishing a plane reference plane by taking the geometric center as the center of the reference plane and taking any reference axis of the three-dimensional space as the normal line of the plane reference plane.
In an embodiment, the method further comprises:
the confirmation instructions are collected from the user's brain infrared signals.
In one embodiment, generating the cross-sectional view of the protein to be observed with reference to the datum plane includes:
taking the intersection surface of the reference surface and the three-dimensional image as a cross section position, and performing Boolean subtraction on the three-dimensional image of the protein to be observed to generate a cross section diagram of the protein to be observed;
and displaying the cross-sectional view through the display module.
In order to achieve the above objective, an embodiment of the present application further provides a protein cross section generating device based on brain infrared control, including:
the terminal is used for establishing a three-dimensional space and loading a three-dimensional image of the protein to be observed;
the display module is connected with the terminal and used for displaying the three-dimensional space in real time;
the establishing module is used for establishing a reference plane in the three-dimensional space;
the brain infrared controller is used for collecting brain infrared signals of a user in real time and adjusting the reference surface according to the brain infrared signals, and the brain infrared controller is also used for controlling a terminal to generate a section view of the protein to be observed by taking the reference surface as a reference.
To achieve the above objective, an embodiment of the present application further provides a protein cross section generating device based on brain infrared control, including a memory, a processor, and a protein cross section generating program based on brain infrared control stored on the memory and capable of running on the processor, where the processor implements the protein cross section generating method based on brain infrared control according to any one of the above when executing the protein cross section generating program based on brain infrared control.
To achieve the above object, an embodiment of the present application further provides a computer readable storage medium, where a protein cross section generating program based on brain infrared control is stored, where the protein cross section generating program based on brain infrared control implements the protein cross section generating method based on brain infrared control according to any one of the above when executed by a processor.
According to the protein cross section generation method based on the brain infrared control, the reference surface is established in the three-dimensional space, the brain infrared of the user is used for adjusting the reference surface in the three-dimensional space, and finally the reference surface is used as a reference to generate a cross section of the protein to be observed, so that any required protein cross section can be generated without inputting complex parameters, and the technical difficulty of acquiring the protein cross section is reduced; in addition, the mode of controlling the movable reference plane by brain infrared does not need to carry out voice or action operation (hand operation or foot operation) by a user, so that the required protein section view can be obtained under the condition of inconvenient voice or action, and the applicability of the protein section is improved. Therefore, compared with the traditional method for generating the protein cross-sectional diagram by setting complex parameters, the method has the advantages of convenience in operation and wide applicability.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an embodiment of a protein cross-section generating apparatus based on brain infrared control according to the present invention;
FIG. 2 is a schematic flow chart of an embodiment of a method for generating a protein cross section based on brain infrared control according to the present invention;
FIG. 3 is a schematic flow chart of an embodiment of a method for generating a protein cross section based on brain infrared control according to the present invention;
FIG. 4 is a schematic flow chart of an embodiment of a method for generating a protein cross section based on brain infrared control according to the present invention;
FIG. 5 is a block diagram showing an embodiment of a protein cross-section generating apparatus based on brain infrared control according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In order that the above-described aspects may be better understood, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. And the use of "first," "second," and "third," etc. do not denote any order, and the terms may be construed as names.
As shown in fig. 1, fig. 1 is a schematic structural diagram of a server 1 (also called a protein cross-section generating device based on brain infrared control) of a hardware running environment according to an embodiment of the present invention.
The server provided by the embodiment of the invention is equipment with a display function, such as 'Internet of things equipment', AR/VR equipment with a networking function, a PC, a smart phone, a tablet personal computer, a portable computer and the like.
As shown in fig. 1, the server 1 includes: memory 11, processor 12 and network interface 13.
The memory 11 includes at least one type of readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the server 1, such as a hard disk of the server 1. The memory 11 may in other embodiments also be an external storage device of the server 1, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the server 1.
Further, the memory 11 may also include an internal storage unit of the server 1 as well as an external storage device. The memory 11 may be used not only for storing application software installed in the server 1 and various types of data, such as codes of the protein cross-section generating program 10 based on brain infrared control, but also for temporarily storing data that has been output or is to be output.
The processor 12 may in some embodiments be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor or other data processing chip for running program code or processing data stored in the memory 11, for example for executing the protein cross-section generating program 10 based on brain infrared control or the like.
The network interface 13 may optionally comprise a standard wired interface, a wireless interface (e.g. WI-FI interface), typically used to establish a communication connection between the server 1 and other electronic devices.
The network may be the internet, a cloud network, a wireless fidelity (Wi-Fi) network, a Personal Area Network (PAN), a Local Area Network (LAN), and/or a Metropolitan Area Network (MAN). Various devices in a network environment may be configured to connect to a communication network according to various wired and wireless communication protocols. Examples of such wired and wireless communication protocols may include, but are not limited to, at least one of the following: transmission control protocol and internet protocol (TCP/IP), user Datagram Protocol (UDP), hypertext transfer protocol (HTTP), file Transfer Protocol (FTP), zigBee, EDGE, IEEE 802.11, light fidelity (Li-Fi), 802.16, IEEE 802.11s, IEEE 802.11g, multi-hop communications, wireless Access Points (APs), device-to-device communications, cellular communication protocol and/or bluetooth (bluetooth) communication protocol, or combinations thereof.
Optionally, the server may further comprise a user interface, which may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or a display unit, for displaying information processed in the server 1 and for displaying a visual user interface.
Fig. 1 shows only a server 1 with components 11-13 and a protein cross-section generating program 10 based on brain infrared control, it will be understood by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the server 1, and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
In this embodiment, the processor 12 may be configured to call a protein section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
establishing a three-dimensional space in a terminal, and loading a three-dimensional image of a protein to be observed in the three-dimensional space;
mapping the three-dimensional space to a display module connected with the terminal in real time;
establishing a reference plane in the three-dimensional space;
collecting brain infrared signals of a user in real time, and adjusting the reference surface according to the brain infrared signals;
and after receiving the confirmation instruction, generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
identifying the type of the current brain infrared signal according to the pre-trained digital classification model;
confirming a preset adjustment instruction corresponding to the current brain infrared signal;
and adjusting the reference surface based on the preset adjustment instruction.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
establishing a corresponding table of the adjusting instruction and the digital visual object;
displaying the digital visual object in the corresponding table of the adjusting instruction and the digital visual object to a user;
collecting brain infrared signals when a user observes the digital visual object, and pre-classifying the collected brain infrared signals to establish a historical brain infrared database of the user;
establishing a digital classification model for classifying the brain infrared signals;
and training the digital classification model based on a historical brain infrared database of the user until the training of the digital classification model is completed.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
and carrying out noise reduction treatment on the acquired brain infrared signals.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
acquiring the geometric center of the three-dimensional image of the protein to be observed;
and establishing a plane reference plane by taking the geometric center as the center of the reference plane and taking any reference axis of the three-dimensional space as the normal line of the plane reference plane.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
the confirmation instructions are collected from the user's brain infrared signals.
In one embodiment, the processor 12 may be configured to call a protein cross-section generation program based on brain infrared control stored in the memory 11, and perform the following operations:
taking the intersection surface of the reference surface and the three-dimensional image as a cross section position, and performing Boolean subtraction on the three-dimensional image of the protein to be observed to generate a cross section diagram of the protein to be observed;
and displaying the cross-sectional view through the display module.
Based on the hardware framework of the protein section generating device based on the brain infrared control, the embodiment of the protein section generating method based on the brain infrared control is provided. The invention discloses a protein section generation method based on brain infrared control, which aims at simplifying a section generation mode of protein.
Referring to fig. 2, fig. 2 is an embodiment of a protein cross-section generating method based on brain infrared control according to the present invention, the protein cross-section generating method based on brain infrared control includes the following steps:
s10, establishing a three-dimensional space in the terminal, and loading a three-dimensional image of the protein to be observed in the three-dimensional space.
The terminal may be a local computing device, such as a PC, a portable computer, a tablet computer, a local server, or a cloud computing device, such as a cloud server.
In particular, the desired three-dimensional space may be established by enabling a specific three-dimensional program, such as UG, solidWorks, 3Dmax, blender, etc., on the terminal. After the establishment of the three-dimensional space is completed, loading the data of the protein to be observed, and generating a three-dimensional image of the corresponding protein in the three-dimensional space. The three-dimensional image is capable of sufficiently exhibiting the stereoscopic shape of the protein to be observed.
And S20, mapping the three-dimensional space to a display module connected with the terminal in real time.
The display module may be a display screen integrated by the terminal itself, or an external display, a projector, or the like connected to the terminal.
Specifically, after the three-dimensional image of the protein to be observed is loaded into the three-dimensional space, the content of the three-dimensional space can be displayed in real time through the display module, so that a user can more intuitively observe the shape and structure of the protein to be observed in the three-dimensional space, and the position of the reference surface in the three-dimensional space can be conveniently and intuitively adjusted by the user.
S30, establishing a reference plane in the three-dimensional space.
Specifically, when the reference plane is established in the three-dimensional space, the method can be realized by the following steps:
s31, acquiring the geometric center of the three-dimensional image of the protein to be observed.
The geometric center of the three-dimensional image is the geometric center of the protein to be observed. Specifically, when calculating the geometric center of the protein to be observed, the three-dimensional image may be equivalent to a regular polyhedron, such as a regular tetrahedron, a regular pentahedron, a regular hexahedron, etc., and the geometric center of the protein to be observed may be obtained based on the equivalent regular polyhedron.
S32, taking the geometric center as the center of the reference surface, and taking any reference axis of the three-dimensional space as the normal line of the plane reference surface to establish the plane reference surface.
The three-dimensional space is established according to the X axis, the Y axis and the Z axis which are perpendicular to each other, so that any one of the X axis, the Y axis and the Z axis can be taken as the normal line of the plane when the plane reference plane is established.
Further, after the center and normal of the planar reference surface are established, the desired planar reference surface can be established accordingly.
Specifically, after the brain infrared control is connected to the terminal, a reference plane may be established in a three-dimensional space of the terminal based on the brain infrared control, the reference plane being movable in the three-dimensional space.
S40, acquiring brain infrared signals of a user in real time, and adjusting the reference surface according to the brain infrared signals.
Among these, spontaneous biopotential of the cerebral cortex of the brain can be amplified from the scalp of the user by a precise instrument and recorded as a brain infrared image to obtain brain infrared signals of the user.
Specifically, since the brain infrared signals may reflect the brain activity of the user, the brain infrared signals of the user may be analyzed to determine adjustments the user wants to make in three-dimensional space, and thus adjust the reference plane in three-dimensional space in real time. Therefore, the reference surface can be adjusted without any voice or action operation (hand operation or foot operation) by the user, so that the technical requirement for adjusting the reference surface is low, and the adjustment of the reference surface can be completed under the condition that the hand of the user is inconvenient (such as the condition that the hand is disabled), thereby greatly facilitating the use of the user.
S50, after receiving the confirmation instruction, generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference.
Specifically, when the reference plane is adjusted in the three-dimensional space, if the reference plane moves to the section position required by any user, a confirmation instruction can be sent to the terminal, and after the terminal receives the corresponding confirmation instruction, the interface between the reference plane and the three-dimensional image can be taken as the section, so that a section view of the protein to be observed can be generated.
It can be understood that according to the protein cross section generation method based on brain infrared control, a reference plane is established in a three-dimensional space, the reference plane in the three-dimensional space is adjusted through the brain infrared of a user, and finally, a cross section of protein to be observed is generated by taking the reference plane as a reference, so that any required protein cross section can be generated without inputting complex parameters, and the technical difficulty of acquiring the protein cross section is reduced; in addition, the mode of controlling the movable reference plane by brain infrared does not need to carry out voice or action operation (hand operation or foot operation) by a user, so that the required protein section view can be obtained under the condition of inconvenient voice or action, and the applicability of the protein section is improved. Therefore, compared with the traditional method for generating the protein cross-sectional diagram by setting complex parameters, the method has the advantages of convenience in operation and wide applicability.
As shown in fig. 3, in an embodiment, adjusting the reference plane according to the brain infrared signal includes:
s110, identifying the type of the current brain infrared signal according to the pre-trained digital classification model.
Specifically, the pre-trained digital classification model is built based on a compressed and excited neural network (i.e., SENet). Through the digital classification model which is finished through pre-training, the currently acquired brain infrared signal images of the user can be classified, and then the type of the current brain infrared signal can be identified.
S120, confirming a corresponding preset adjustment instruction of the current brain infrared signal.
Specifically, after the digital classification model identifies the type of the current brain infrared signal, the preset adjustment instruction corresponding to the current brain infrared signal can be further searched according to the preset brain infrared-adjustment instruction corresponding table, where the adjustment instruction refers to an instruction used by the input terminal to adjust the reference plane, such as rotation, movement, amplification, shrinkage, and the like.
S130, adjusting the reference surface based on the preset adjusting instruction.
Specifically, after the adjustment instruction corresponding to the current brain infrared is determined, the reference plane can be correspondingly adjusted according to the adjustment instruction.
It should be noted that, because the brain infrared signal of the user is collected in real time, the reference plane can be continuously adjusted according to the brain infrared signal of the user before the confirmation signal is received.
It can be understood that the brain infrared of the user is classified and identified through the pre-training digital classification model, so that the interference of the ineffective brain infrared on the adjustment of the reference surface can be reduced, and the accuracy of the adjustment of the reference surface can be improved.
As shown in fig. 4, in an embodiment, before collecting the brain infrared signals of the user, the method further comprises:
s210, establishing a corresponding table of the adjusting instruction and the digital visual object.
The digital visual object is used for stimulating the vision of a user so as to enable the user to generate a digital object corresponding to brain infrared, such as Arabic numerals, chinese numerals and the like.
Specifically, the adjustment instruction and digital visual object corresponding table refers to a table in which adjustment instructions and digital visual objects are in one-to-one correspondence, and the table defines adjustment instructions represented by different digital visual objects, such as a horizontal reference plane corresponding to a palm flattening gesture. It should be noted that the adjustment instruction and the adjustment instruction in the digital visual object table and the corresponding digital visual object can be adaptively adjusted according to the actual situation.
S220, displaying the digital visual object in the corresponding table of the adjusting instruction and the digital visual object to the user.
Specifically, after the adjustment instruction and digital visual object corresponding table is established, the digital visual objects in the table can be displayed to the user one by one, so that the corresponding digital visual objects are generated in the mind of the user, and the impression of the user on different digital visual objects is deepened. For example, when a user views a red-colored digital visual object, the user's brain infrared at that time is obviously associated with the red-colored digital visual object.
S230, collecting brain infrared signals when a user observes the digital visual object, and pre-classifying the collected brain infrared signals to establish a historical brain infrared database of the user.
Specifically, when the user observes the corresponding digital visual object, a corresponding impression is generated in the brain, so that the brain infrared generated by the user at the moment can be considered to be matched with the observed digital visual object, and the currently acquired brain infrared can be classified into the corresponding digital visual object so as to establish a required historical brain infrared database. For example, when the user observes a digital visual object of the number "1", the user brain infrared rays acquired at this time may be classified as brain infrared rays corresponding to the object of the number "1".
In addition, the targeted object stimulation can reduce noise in the acquired database, improve the quality of the database and improve the training precision of the model.
S240, establishing a digital classification model for classifying the brain infrared signals.
In particular, a desired digital classification model may be built based on a convolutional neural network.
S250, training the digital classification model based on a historical brain infrared database of the user until the training of the digital classification model is completed.
Specifically, according to the digital classification model trained by the pertinently acquired historical brain infrared database, a high-precision digital classification model can be obtained, and further the precision of reference plane adjustment can be improved.
It can be understood that by establishing a preset corresponding table of adjusting instructions and digital visual objects, stimulating the vision generated by a user by using the corresponding table, generating corresponding brain infrared signals in the brain of the user, establishing a brain infrared database of the user by using the brain infrared signals, and training the digital classification model, the digital classification model with high precision can be obtained, and the precision passing through the brain infrared reference plane is improved.
In one embodiment, before pre-classifying the acquired brain infrared signals, the method further comprises:
and carrying out noise reduction treatment on the acquired brain infrared signals.
Specifically, noise reduction processing is performed on the brain infrared signals, namely, filtering processing is performed on the data of the brain infrared signals, so that noise in the collected brain infrared data is filtered. The operation can improve the data quality of the acquired brain infrared data so as to acquire a high-precision digital classification model, and further the precision of reference plane adjustment is improved.
In an embodiment, the method further comprises:
the confirmation instructions are collected from the user's brain infrared signals.
That is, after the reference plane is adjusted at the required position, the user can imagine the digital visual object corresponding to the confirmation instruction in mind, further generate a brain infrared signal matched with the adjustment instruction, and the terminal can consider that the confirmation instruction is received after acquiring the corresponding brain infrared signal. It can be understood that the user can finish the adjustment of the reference plane and the confirmation of the protein section only by brain infrared, so that the operation modes of the user can be more uniform, and the user operation is facilitated. Of course, the design of the present application is not limited thereto, and in other embodiments, the confirmation instructions may also come from a separate switch module, such as a separate manual switch, foot switch, or the like.
In one embodiment, generating the cross-sectional view of the protein to be observed with reference to the datum plane includes:
s310, taking the intersection surface of the reference surface and the three-dimensional image as a cross-section position, and performing Boolean subtraction on the three-dimensional image of the protein to be observed to generate a cross-section diagram of the protein to be observed.
Among these, the boolean subtraction operation is the bool subtraction operation. Specifically, when a protein cross section is generated, the cross section of the protein to be observed at the current position can be obtained by performing Boolean subtraction on the three-dimensional image of the protein to be observed by taking the intersection surface of the current reference surface and the three-dimensional image of the protein to be observed as the cross section position.
S320, displaying the cross-section through the display module.
Specifically, after the cross-sectional view of the protein to be observed is generated, the cross-sectional view may be displayed by the display module, so that the user may observe the truncated cross-sectional view of the protein in real time. The user may then determine whether to reacquire a new protein profile based on the current protein profile.
Based on the above embodiments, the protein section generating method based on the brain infrared control of the application is exemplified and specifically comprises the following steps: firstly, a user can see different numbers, data of brain infrared signals are generated through visual stimulation, the data are filtered and then are used for training a digital classification model (the digital classification model is used for converting real-time brain infrared signals into corresponding numbers, the different numbers correspond to different control instructions (namely adjustment instructions) through codes), and after the training of the digital classification model is completed, the real-time brain infrared control can be carried out. Specifically, the coding rule of the present invention is: the number 1 corresponds to a horizontal section operation, the number 2 represents a vertical section operation, the number 3 represents a section operation parallel to a computer screen, the number 4 represents a confirmation operation, the number 5 represents a decrease in coordinates, and the number 6 represents an increase in coordinates. When the virtual section reaches a satisfactory direction, a user can generate a confirmation signal by only imagining the number 4, and after receiving the confirmation signal, the computer performs a bool subtraction operation on the three-dimensional image to complete the generation and display of the section graph.
In addition, referring to fig. 5, an embodiment of the present invention further provides a protein cross section generating device based on brain infrared control, where the protein cross section generating device based on brain infrared control includes:
a terminal 110 for creating a three-dimensional space and loading a three-dimensional image of a protein to be observed;
the display module 120 is connected with the terminal and is used for displaying the three-dimensional space in real time;
a building module 130, configured to build a reference plane in the three-dimensional space;
the brain infrared controller 140 is configured to collect brain infrared signals of a user in real time, adjust the reference plane according to the brain infrared signals, and control a terminal to generate a cross-sectional view of the protein to be observed with the reference plane as a reference.
The steps implemented by each functional module of the protein cross section generating device based on brain infrared control can refer to each embodiment of the protein cross section generating method based on brain infrared control, and are not described herein.
In addition, the embodiment of the invention also provides a computer readable storage medium, which can be any one or any combination of a plurality of hard disk, a multimedia card, an SD card, a flash memory card, an SMC, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory and the like. The computer readable storage medium includes a protein cross section generating program 10 based on brain infrared control, and the specific embodiment of the computer readable storage medium of the present invention is substantially the same as the above-mentioned protein cross section generating method based on brain infrared control and the specific embodiment of the server 1, and will not be described herein.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. A protein cross-section generation method based on brain infrared control, which is characterized by comprising the following steps:
establishing a three-dimensional space in a terminal, and loading a three-dimensional image of a protein to be observed in the three-dimensional space;
mapping the three-dimensional space to a display module connected with the terminal in real time;
establishing a reference plane in the three-dimensional space;
collecting brain infrared signals of a user in real time, and adjusting the reference surface according to the brain infrared signals;
after receiving the confirmation instruction, generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference; wherein, the liquid crystal display device comprises a liquid crystal display device,
establishing a reference plane in the three-dimensional space, including:
acquiring the geometric center of the three-dimensional image of the protein to be observed;
establishing a plane reference plane by taking the geometric center as the center of the reference plane and taking any reference axis of the three-dimensional space as the normal line of the plane reference plane;
generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference, wherein the cross-sectional view comprises:
taking the intersection surface of the reference surface and the three-dimensional image as a cross section position, and performing Boolean subtraction on the three-dimensional image of the protein to be observed to generate a cross section diagram of the protein to be observed;
and displaying the cross-sectional view through the display module.
2. The method for generating a protein cross section based on brain infrared control according to claim 1, wherein adjusting the reference plane according to the brain infrared signal comprises:
identifying the type of the current brain infrared signal according to the pre-trained digital classification model;
confirming a preset adjustment instruction corresponding to the current brain infrared signal;
and adjusting the reference surface based on the preset adjustment instruction.
3. The brain infrared control based protein cross-section generating method according to claim 2, wherein before collecting the brain infrared signals of the user, the method further comprises:
establishing a corresponding table of the adjusting instruction and the digital visual object;
displaying the digital visual object in the corresponding table of the adjusting instruction and the digital visual object to a user;
collecting brain infrared signals when a user observes the digital visual object, and pre-classifying the collected brain infrared signals to establish a historical brain infrared database of the user;
establishing a digital classification model for classifying the brain infrared signals;
and training the digital classification model based on a historical brain infrared database of the user until the training of the digital classification model is completed.
4. A method of protein cross-section generation based on brain infrared control according to claim 3, wherein prior to pre-classifying the acquired brain infrared signals, the method further comprises:
and carrying out noise reduction treatment on the acquired brain infrared signals.
5. The brain infrared control based protein cross-section generation method according to claim 1, wherein said method further comprises:
the confirmation instructions are collected from the user's brain infrared signals.
6. A protein cross-section generating device based on brain infrared control, comprising:
the terminal is used for establishing a three-dimensional space and loading a three-dimensional image of the protein to be observed;
the display module is connected with the terminal and used for displaying the three-dimensional space in real time;
the establishing module is used for establishing a reference plane in the three-dimensional space;
the brain infrared controller is used for collecting brain infrared signals of a user in real time and adjusting the reference surface according to the brain infrared signals, and the brain infrared controller is also used for controlling a terminal to generate a cross-sectional view of the protein to be observed by taking the reference surface as a reference; wherein, the liquid crystal display device comprises a liquid crystal display device,
the establishing module establishes a reference plane in the three-dimensional space, including:
acquiring the geometric center of the three-dimensional image of the protein to be observed;
establishing a plane reference plane by taking the geometric center as the center of the reference plane and taking any reference axis of the three-dimensional space as the normal line of the plane reference plane;
the brain infrared controller control terminal generating a cross-sectional view of the protein to be observed by taking the datum plane as a reference comprises:
taking the intersection surface of the reference surface and the three-dimensional image as a cross section position, and performing Boolean subtraction on the three-dimensional image of the protein to be observed to generate a cross section diagram of the protein to be observed;
and displaying the cross-sectional view through the display module.
7. A protein section generating device based on brain infrared control, characterized by comprising a memory, a processor and a protein section generating program based on brain infrared control, wherein the protein section generating program based on brain infrared control is stored on the memory and can be run on the processor, and the processor realizes the protein section generating method based on brain infrared control according to any one of claims 1-5 when executing the protein section generating program based on brain infrared control.
8. A computer-readable storage medium, wherein a protein cross-section generating program based on brain infrared control is stored on the computer-readable storage medium, and when the protein cross-section generating program based on brain infrared control is executed by a processor, the protein cross-section generating method based on brain infrared control according to any one of claims 1 to 5 is realized.
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| WO2004090100A2 (en) * | 2003-04-04 | 2004-10-21 | Agilent Technologies, Inc. | Visualizing expression data on chromosomal graphic schemes |
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| 王雪平 等."基于统计方法描述的蛋白质三维结构相似性比较".《闽南师范大学学报(自然科学版) 》.2014,全文. * |
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