Cell number measuring method applied to biological information

Abstract

The invention discloses a cell quantity measurement method applied to biological information, relates to the technical field of cell measurement, is used for improving cell suspension polymerization conditions and increasing cell quantity measurement errors, and comprises the following steps: calling information of a culture medium in which to-be-measured cells are located, analyzing suspension changes of the to-be-measured cells in combination with culture time intervals, and determining the cell quantity of the to-be-measured cells. Setting a suspension threshold value by using a logarithmic binding method, screening out suspension cells in a culture dish according to the suspension threshold value, setting a plurality of monitoring intervals, monitoring the cell activity and the cell cycle of each monitoring interval, and adjusting each monitoring area to generate a cell level, carrying out quantity statistics on the suspension cells of each cell level to obtain level density, measuring the size of the suspension cells, and determining the maximum cell polymerization quantity of each cell level; and fusing the hierarchy density and the maximum cell polymerization amount, calculating the suspension aggregation index of each cell hierarchy by using a polynomial regression algorithm, converting the suspension aggregation index into a measurement error value caused by suspension cells, and marking a culture dish according to the measurement error value for cell measurement.

Description

Technical Field

[0001] The present invention relates to the technical field of cell measurement, and more particularly to a method for measuring the number of cells applied to biological information. Background Art

[0002] Cell measurement technology is a method used to quantitatively and qualitatively analyze cell characteristics and behaviors. Cell measurement technology is applied to biological information and can provide more accurate biological cell data, which helps to improve the project efficiency of biological experiments or cell technology.

[0003] The prior art has the following deficiencies: In the past, when measuring the number of cells in biological targets, in order to facilitate measurement, cell samples were first extracted from the target and placed in a culture dish for measurement. However, before measurement, due to mutual attraction between cells and problems with the culture medium material, some cells became suspended or aggregated, increasing the measurement error of the underlying cells and affecting the progress and accuracy of the results of the biological project. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a cell number measurement method applied to biological information, which screens suspended cells and divides the suspension area through culture information, sets a monitoring interval in the culture dish to generate a cell level analysis of the suspension aggregation of suspended cells, and judges whether to use the current culture dish for cell measurement to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: The method for measuring the number of cells applied to bioinformatics comprises the following steps: Step S1: Retrieve the culture medium information of the cells to be tested, analyze the suspension changes of the cells to be tested in combination with the culture time interval, and set the suspension threshold value based on the default suspension amount of the culture medium information and the suspension changes of the cells to be tested; Step S2: screening out suspended cells according to the suspension threshold and determining the suspended cell area of ​​the culture dish, setting multiple monitoring intervals in the suspended cell area of ​​the culture dish, detecting the cell activity and cell cycle of each monitoring interval and calculating the stratification coefficient, and adjusting each monitoring interval according to the stratification coefficient to generate a cell hierarchy; Step S3: Counting the number of suspended cells in each cell layer to obtain the layer density, randomly selecting a plurality of suspended cells in each cell layer to measure their size, and determining the maximum cell aggregation amount of each cell layer according to the size measurement results; Step S4: The suspension aggregation index of each cell layer is calculated by comprehensively considering the layer density of each cell layer and the maximum cell aggregation amount using a polynomial regression algorithm, and the suspension aggregation index of each cell layer is converted into a measurement error value caused by suspended cells. According to the measurement error value caused by suspended cells, culture dishes are selected for marking, and the marked culture dishes are screened for cell measurement.

[0006] In a preferred embodiment, in step S1, the culture medium information is the growth factor concentration, the time point when the cells are transferred to the culture dish is recorded, and a second record is made when the suspension change is measured, and the time interval between the two time points is used as the culture time interval; For each culture dish, combined with the growth factor concentration and culture time interval, the logarithmic binding method is used to analyze the suspension changes of the cells to be tested and set the suspension threshold.

[0007] In a preferred embodiment, in step S1, the logarithmic binding method is used to analyze the suspension change of the cells to be tested and set the suspension threshold, and the specific steps are as follows: Data preprocessing: The growth factor concentration and culture time of each culture dish were standardized and merged into the factor concentration data set and culture time data set respectively; Establish a suspension change system: randomly select a data in the factor concentration data set and the culture time data set for factor combination: , where x is the data selected from the factor concentration data set, y is the data selected from the culture time data set, and H is the culture dish suspension coefficient obtained by calculation; Set the number of system executions: Set the number of system executions to n times, and obtain the suspension coefficients of n culture dishes by randomly selecting n data from the factor concentration data set and the culture time data set; Set the suspension threshold: Use the average values ​​of the factor concentration data set and the culture time data set to establish a suspension change system and calculate the culture dish suspension coefficient as the suspension calibration value. Calculate the average value of the obtained n culture dish suspension coefficients as the true suspension value, and set the suspension threshold through the suspension threshold adjustment formula: ,in, is the true value of the suspension, is the suspension calibration value, It is the default floating space. is the floating threshold.

[0008] The default suspension space is the suspension space of the cells to be tested in the culture dish where the corresponding culture dish is located that has been stored in the cell information management system.

[0009] In a preferred embodiment, in step S2, the space of the culture dish within the suspension threshold is used as the suspension cell area, and the cells to be tested in the suspension cell area in each culture dish are used as the suspension cells in the corresponding culture dish;

[0010] A plurality of monitoring areas are set from top to bottom in the suspended cell area according to a preset ratio, the suspended cells in each monitoring area are counted and the survival rate of the suspended cells in the corresponding monitoring area is calculated, the cell cycle of the suspended cells in each monitoring area is detected and the proportion of each cycle stage is counted.

[0011] In a preferred embodiment, in step S2, the cell migration coefficient of each monitoring area is obtained by weighted summing the cycle phase proportion of the suspended cells in each monitoring area and the migration weight preset in each cell cycle;

[0012] The stratification coefficient was calculated by using a logistic regression algorithm based on the survival rate of suspended cells and the cell migration coefficient in each monitoring area. The specific steps are as follows: The logistic regression formula is constructed using the survival rate of suspended cells in the monitoring area and the cell migration coefficient of the corresponding monitoring area: , where e is the natural base, z is the influencing parameter and z is the sum of the survival rate of suspended cells and the cell migration coefficient in the corresponding monitoring area, and L is the stratification coefficient of the corresponding monitoring area calculated by the logistic regression formula; The same processing is performed on each monitoring area to obtain the stratification coefficient of each monitoring area. The average stratification coefficient of all monitoring areas is taken as the stratification benchmark. The stratification coefficient of each monitoring area is changed by adjusting the spatial size occupied by each monitoring area. When the stratification coefficient of each monitoring area reaches the stratification benchmark, the spatial size of each monitoring area is adjusted, and the adjusted monitoring areas are generated as cell levels.

[0013] In a preferred embodiment, in step S3, the suspended cells in each cell layer are counted to obtain the layer density, and the layer density is the ratio of the number of suspended cells in each cell layer to the volume of the corresponding cell layer space;

[0014] In each cell level, a plurality of suspended cells are randomly selected for size measurement and the average value is calculated as the size standard of the suspended cells in the corresponding cell level. The suspended cells in each cell level are judged according to the preset single cell judgment conditions. The suspended cells with the largest size in each cell level are selected for size recording. The size recording result is used as the size to be assessed in the corresponding cell level. The size to be assessed in each cell level is compared with the size standard of the suspended cells in the corresponding cell level to determine the maximum cell aggregation amount in each cell level.

[0015] In a preferred embodiment, in step S3, the specific steps of determining the maximum cell aggregation amount of each cell level according to the size measurement results are as follows: The ratio of the size to be assessed at each cell level to the size standard of suspended cells in the corresponding cell level is used as the cell amount assessment parameter of the corresponding cell level, and the cell amount assessment parameter of each cell level is rounded up as the maximum cell aggregation amount of the corresponding cell level.

[0016] In a preferred embodiment, in step S4, the suspension aggregation index of each cell layer is calculated by using a polynomial regression algorithm based on the layer density of each cell layer and the maximum cell aggregation amount. The specific steps are as follows: Normalized input: The Max-Min algorithm was used to normalize the cell layer density and the maximum cell aggregation; Constructing a polynomial regression formula: Constructing a polynomial regression formula based on the normalized results of the layer density of each cell layer and the maximum cell aggregation amount: , where a is the normalized result of the layer density of each cell layer, b is the normalized result of the maximum cell aggregation amount of each cell layer, c is the preset adjustment parameter, and F is the suspension aggregation index.

[0017] The adjustment parameter c is used to control the numerical range of the suspension aggregation index.

[0018] In a preferred embodiment, in step S4, the suspension aggregation index of each cell level is converted into the measurement error value caused by the suspended cells using the conversion formula: , where C is the measurement error caused by the suspended cells in each culture dish, and s is the conversion ratio; The measurement error value caused by the suspended cells in each culture dish is compared with the preset error threshold. If the measurement error value caused by the suspended cells in the current culture dish exceeds the error threshold, the current culture dish is discarded and the cell number measurement is not performed; if the measurement error value caused by the suspended cells in the current culture dish is lower than the error threshold, the current culture dish is marked and the cell number measurement is performed.

[0019] The technical effects and advantages of the cell number measurement method applied to biological information of the present invention are as follows: The present invention retrieves the culture medium information of the cells to be tested, analyzes the suspension changes of the cells to be tested in combination with the culture time interval, sets the suspension threshold value based on the default suspension amount of the culture medium information and the suspension change of the cells, screens out the suspended cells in the culture dish according to the suspension threshold value, avoids the fuzzy definition of suspension leading to a decrease in the accuracy of subsequent analysis, sets multiple monitoring intervals to monitor the cell activity and cell cycle in each monitoring interval and calculates the stratification coefficient, adjusts each monitoring area according to the stratification coefficient to generate a cell hierarchy, the cell hierarchy is used to reduce the tolerance error of subsequent statistical cell distribution density, performs quantitative statistics on the suspended cells of each cell hierarchy to obtain the hierarchy density, measures the size of the suspended cells, determines the maximum cell aggregation amount of each cell hierarchy, comprehensively obtains the hierarchy density and the maximum cell aggregation amount of each cell hierarchy, calculates the suspension aggregation index of each cell hierarchy and converts it into a measurement error value caused by the suspended cells, marks the culture dish according to the measurement error value to perform cell measurement, and reduces the cell data measurement error caused by the suspended cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the cell quantity measurement method applied to biological information according to the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] The present invention retrieves the culture medium information of the cells to be tested, analyzes the suspension changes of the cells to be tested in combination with the culture time interval, sets the suspension threshold value based on the suspension change of the cells according to the default suspension amount of the culture medium information, screens out the suspended cells in the culture dish according to the suspension threshold value, sets a plurality of monitoring intervals to monitor the cell activity and cell cycle in each monitoring interval and calculates the stratification coefficient, adjusts each monitoring area according to the stratification coefficient to generate a cell hierarchy, performs quantitative statistics on the suspended cells in each cell hierarchy to obtain the hierarchy density, measures the size of the suspended cells, determines the maximum cell aggregation amount of each cell hierarchy, comprehensively obtains the hierarchy density and the maximum cell aggregation amount of each cell hierarchy, calculates the suspension aggregation index of each cell hierarchy and converts it into a measurement error value caused by the suspended cells, marks the culture dish according to the measurement error value to perform cell measurement, and reduces the cell data measurement error caused by the suspended cells.

[0023] Embodiment, the cell data measurement method applied to biological information, such as Figure 1 As shown, the following steps are included: Step S1: Retrieve the culture medium information of the cells to be tested, analyze the suspension changes of the cells to be tested in combination with the culture time interval, and set the suspension threshold value based on the default suspension amount of the culture medium information and the suspension changes of the cells to be tested; Step S2: screening out suspended cells according to the suspension threshold and determining the suspended cell area of ​​the culture dish, setting multiple monitoring intervals in the suspended cell area of ​​the culture dish, detecting the cell activity and cell cycle of each monitoring interval and calculating the stratification coefficient, and adjusting each monitoring interval according to the stratification coefficient to generate a cell hierarchy; Step S3: Counting the number of suspended cells in each cell layer to obtain the layer density, randomly selecting a plurality of suspended cells in each cell layer to measure their size, and determining the maximum cell aggregation amount of each cell layer according to the size measurement results; Step S4: The suspension aggregation index of each cell layer is calculated by comprehensively considering the layer density of each cell layer and the maximum cell aggregation amount using a polynomial regression algorithm, and the suspension aggregation index of each cell layer is converted into a measurement error value caused by suspended cells. According to the measurement error value caused by suspended cells, culture dishes are selected for marking, and the marked culture dishes are screened for cell measurement.

[0024] The specific implementation is as follows: In step S1: access the cell information management system to retrieve the culture medium information of the cells to be tested, the culture medium information is the concentration of growth factors, and the cells of the target body need to be transferred and cultured before measuring the cell number. Usually, multiple locations on the target body are randomly selected, and equal amounts of samples are extracted and transferred to culture dishes of the same material for storage. The cell number range of the target body is obtained by measuring cells in multiple culture dishes respectively; The time point when the cells were transferred to the culture dish was recorded, and a second record was made when the suspension change was measured, and the time interval between the two time points was used as the culture time interval; For each culture dish, combined with the growth factor concentration and culture time interval, the logarithmic binding method is used to analyze the suspension changes of the cells to be tested and set the suspension threshold. The specific steps are as follows: Data preprocessing: The growth factor concentration and culture time of each culture dish were standardized and merged into the factor concentration data set and culture time data set respectively; Establish a suspension change system: randomly select a data in the factor concentration data set and the culture time data set for factor combination: , where x is the data selected from the factor concentration data set, y is the data selected from the culture time data set, and H is the culture dish suspension coefficient obtained by calculation; Set the number of system executions: Set the number of system executions to n times, and obtain the suspension coefficients of n culture dishes by randomly selecting n data from the factor concentration data set and the culture time data set; Set the suspension threshold: Use the average values ​​of the factor concentration data set and the culture time data set to establish a suspension change system and calculate the culture dish suspension coefficient as the suspension calibration value. Calculate the average value of the obtained n culture dish suspension coefficients as the true suspension value, and set the suspension threshold through the suspension threshold adjustment formula: ,in, is the true value of the suspension, is the suspension calibration value, It is the default floating space. is the floating threshold.

[0025] It should be noted that the cell information management system is a software tool for managing and tracking cell lines and their related data, which includes the culture medium information of the cells to be tested. In this example, it is used to call the growth factor concentration of the culture dish. The higher the growth factor concentration of the culture dish where the cells to be tested are located, the lower the amount of suspended dead cells, the larger the suspension space, the longer the culture time of the cells to be tested, the increased cell sedimentation behavior, and the larger the suspension space; the default suspension space is the suspension space of the cells to be tested in the culture dish where the corresponding culture dish is located that has been stored in the cell information management system. The suspension threshold is geometrically expanded or reduced through the default suspension space to reduce the cell number measurement error caused by suspended cells.

[0026] In step S2, the space of the culture dish within the suspension threshold is regarded as the suspension cell area, and the cells to be tested in the suspension cell area in each culture dish are regarded as the suspension cells in the corresponding culture dish; In the suspended cell area, multiple monitoring areas are set from top to bottom according to a preset ratio, the suspended cells in each monitoring area are counted and the survival rate of the suspended cells in the corresponding monitoring area is calculated, the cell cycle of the suspended cells in each monitoring area is detected and the proportion of each cycle stage is counted; It should be noted that cells in the culture dish will have multiple cell cycles, for example, interphase, cell synthesis phase, and mitosis phase. Each cell cycle will cause cell migration due to specific physiological processes. Cell migration includes cell floating and cell sinking, which will affect the cell suspension trend.

[0027] The cell migration coefficient of each monitoring area is obtained by weighted summing the cycle phase proportion of the suspended cells in each monitoring area and the preset migration weight of each cell cycle;

[0028] The stratification coefficient was calculated by using a logistic regression algorithm based on the survival rate of suspended cells and the cell migration coefficient in each monitoring area. The specific steps are as follows: The logistic regression formula is constructed using the survival rate of suspended cells in the monitoring area and the cell migration coefficient of the corresponding monitoring area: , where e is the natural base, z is the influencing parameter and z is the sum of the survival rate of suspended cells and the cell migration coefficient in the corresponding monitoring area, and L is the stratification coefficient of the corresponding monitoring area calculated by the logistic regression formula; The same processing is performed on each monitoring area to obtain the stratification coefficient of each monitoring area. The average stratification coefficient of all monitoring areas is taken as the stratification benchmark. The stratification coefficient of each monitoring area is changed by adjusting the spatial size occupied by each monitoring area. When the stratification coefficient of each monitoring area reaches the stratification benchmark, the spatial size of each monitoring area is adjusted, and the adjusted monitoring areas are generated as cell levels.

[0029] It should be noted that the generation of cell levels is used to reduce the tolerance error of subsequent statistical cell distribution density, and at the same time, reduce the measurement impact caused by cell movement.

[0030] In step S3, the suspended cells in each cell layer are counted to obtain the layer density, which is the ratio of the number of suspended cells in each cell layer to the volume of the corresponding cell layer space; In each cell level, a plurality of suspended cells are randomly selected for size measurement and the average value is calculated as the size standard of the suspended cells in the corresponding cell level. The suspended cells in each cell level are judged according to the preset single cell judgment condition, and the largest suspended cell in each cell level is selected for size recording. The size recording result is used as the size to be assessed in the corresponding cell level. The size to be assessed in each cell level is compared with the size standard of the suspended cells in the corresponding cell level to determine the maximum cell aggregation amount in each cell level. The specific steps for determining the maximum cell aggregation amount of each cell level based on the size measurement results are as follows: The ratio of the size to be assessed at each cell level to the size standard of suspended cells in the corresponding cell level is used as the cell amount assessment parameter of the corresponding cell level, and the cell amount assessment parameter of each cell level is rounded up as the maximum cell aggregation amount of the corresponding cell level.

[0031] It should be noted that when counting cells, the interaction between cells will cause multiple cells to form aggregates, which will lead to deviations in cell counting. The larger the size to be assessed at each cell level, the greater the interaction between suspended cells in the corresponding cell level, the easier it is to form aggregates, and the greater the deviation in cell counting. In addition, the greater the density of suspended cells, the greater the deviation in bottom cell counting statistics.

[0032] In step S4, the suspension aggregation index of each cell layer is calculated by using a polynomial regression algorithm based on the layer density of each cell layer and the maximum cell aggregation amount. The specific steps are as follows: Normalized input: The Max-Min algorithm is used to normalize the cell layer density and the maximum cell aggregation amount: ,in, is the layer density or maximum cell aggregation of each cell layer, is the maximum value of the layer density or the maximum cell aggregation of all cell layers, is the minimum value of the layer density or the maximum cell aggregation of all cell layers, The results are normalized to the layer density or the maximum cell aggregation of the corresponding cell layer; Constructing a polynomial regression formula: Constructing a polynomial regression formula based on the normalized results of the layer density of each cell layer and the maximum cell aggregation amount: , where a is the normalized result of the layer density of each cell layer, b is the normalized result of the maximum cell aggregation amount of each cell layer, c is the adjustment parameter, and F is the suspension aggregation index.

[0033] It should be explained that in this example, the weight of each parameter in the above polynomial regression formula is set to 1, which can be adjusted according to actual conditions. The adjustment parameter c is used to control the numerical range of the suspension aggregation index, which is convenient for converting it into the measurement error value of suspended cells. The adjustment parameter c is not unique. For example, the adjustment parameter is set to 0.2, etc., which will not be analyzed too much here.

[0034] The suspension aggregation index of each cell level is converted into the measurement error caused by suspended cells using the conversion formula: , where C is the measurement error caused by the suspended cells in each culture dish, and s is the conversion ratio;

[0035] The measurement error value caused by the suspended cells in each culture dish is compared with the preset error threshold. If the measurement error value caused by the suspended cells in the current culture dish exceeds the error threshold, the current culture dish is discarded and the cell number measurement is not performed; if the measurement error value caused by the suspended cells in the current culture dish is lower than the error threshold, the current culture dish is marked and the cell number measurement is performed.

[0036] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0037] Those of ordinary skill in the art will appreciate that the modules 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 of the technical solution and the invention constraints. 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.

[0038] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0039] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0040] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for measuring the number of cells applied to bioinformatics, characterized in that: The following steps are included: Step S1: Retrieve the culture medium information of the cells to be tested, analyze the suspension changes of the cells to be tested in combination with the culture time interval, and set the suspension threshold value based on the default suspension amount of the culture medium information and the suspension changes of the cells to be tested; Step S2: screening out suspended cells according to the suspension threshold and determining the suspended cell area of ​​the culture dish, setting multiple monitoring intervals in the suspended cell area of ​​the culture dish, detecting the cell activity and cell cycle of each monitoring interval and calculating the stratification coefficient, and adjusting each monitoring interval according to the stratification coefficient to generate a cell hierarchy; Step S3: Counting the number of suspended cells in each cell layer to obtain the layer density, randomly selecting a plurality of suspended cells in each cell layer to measure their size, and determining the maximum cell aggregation amount of each cell layer according to the size measurement results; Step S4: The suspension aggregation index of each cell layer is calculated by comprehensively considering the layer density of each cell layer and the maximum cell aggregation amount using a polynomial regression algorithm, and the suspension aggregation index of each cell layer is converted into a measurement error value caused by suspended cells. According to the measurement error value caused by suspended cells, culture dishes are selected for marking, and the marked culture dishes are screened for cell measurement.

2. The method for measuring the number of cells applied to biological information according to claim 1, characterized in that: In step S1, the culture medium information is the growth factor concentration, the time point when the cells are transferred to the culture dish is recorded, and a second record is made when the suspension change is measured, and the time interval between the two time points is used as the culture time interval; For each culture dish, combined with the growth factor concentration and culture time interval, the logarithmic binding method is used to analyze the suspension changes of the cells to be tested and set the suspension threshold.

3. The method for measuring the number of cells applied to biological information according to claim 2, characterized in that: In step S1, the logarithmic binding method is used to analyze the suspension changes of the cells to be tested and set the suspension threshold. The specific steps are as follows: Data preprocessing: The growth factor concentration and culture time of each culture dish were standardized and merged into the factor concentration data set and culture time data set respectively; Establish a suspension change system: randomly select a data in the factor concentration data set and the culture time data set for factor combination: , where x is the data selected from the factor concentration data set, y is the data selected from the culture time data set, and H is the culture dish suspension coefficient obtained by calculation; Set the number of system executions: Set the number of system executions to n times, and obtain the suspension coefficients of n culture dishes by randomly selecting n data from the factor concentration data set and the culture time data set; Set the suspension threshold: Use the average values ​​of the factor concentration data set and the culture time data set to establish a suspension change system and calculate the culture dish suspension coefficient as the suspension calibration value. Calculate the average value of the obtained n culture dish suspension coefficients as the true suspension value, and set the suspension threshold through the suspension threshold adjustment formula: ,in, is the true value of the suspension, is the suspension calibration value, It is the default floating space. is the suspension threshold; The default suspension space is the suspension space of the cells to be tested in the culture dish where the corresponding culture dish is located that has been stored in the cell information management system.

4. The method for measuring the number of cells applied to biological information according to claim 3, characterized in that: In step S2, the space of the culture dish within the suspension threshold is regarded as the suspension cell area, and the cells to be tested in the suspension cell area in each culture dish are regarded as the suspension cells in the corresponding culture dish; A plurality of monitoring areas are set from top to bottom in the suspended cell area according to a preset ratio, the suspended cells in each monitoring area are counted and the survival rate of the suspended cells in the corresponding monitoring area is calculated, the cell cycle of the suspended cells in each monitoring area is detected and the proportion of each cycle stage is counted.

5. The method for measuring the number of cells applied to biological information according to claim 1, characterized in that: In step S2, the cell migration coefficient of each monitoring area is obtained by weighted summing the cycle phase proportion of the suspended cells in each monitoring area and the preset migration weight of each cell cycle; The stratification coefficient was calculated by using a logistic regression algorithm based on the survival rate of suspended cells and the cell migration coefficient in each monitoring area. The specific steps are as follows: The logistic regression formula is constructed using the survival rate of suspended cells in the monitoring area and the cell migration coefficient of the corresponding monitoring area: , where e is the natural base, z is the influencing parameter and z is the sum of the survival rate of suspended cells and the cell migration coefficient in the corresponding monitoring area, and L is the stratification coefficient of the corresponding monitoring area calculated by the logistic regression formula; The same processing is performed on each monitoring area to obtain the stratification coefficient of each monitoring area. The average stratification coefficient of all monitoring areas is taken as the stratification benchmark. The stratification coefficient of each monitoring area is changed by adjusting the spatial size occupied by each monitoring area. When the stratification coefficient of each monitoring area reaches the stratification benchmark, the spatial size of each monitoring area is adjusted, and the adjusted monitoring areas are generated as cell levels.

6. The method for measuring the number of cells applied to biological information according to claim 5, characterized in that: In step S3, the suspended cells in each cell layer are counted to obtain the layer density, which is the ratio of the number of suspended cells in each cell layer to the volume of the corresponding cell layer space; In each cell level, a plurality of suspended cells are randomly selected for size measurement and the average value is calculated as the size standard of the suspended cells in the corresponding cell level. The suspended cells in each cell level are judged according to the preset single cell judgment conditions. The suspended cells with the largest size in each cell level are selected for size recording. The size recording result is used as the size to be assessed in the corresponding cell level. The size to be assessed in each cell level is compared with the size standard of the suspended cells in the corresponding cell level to determine the maximum cell aggregation amount in each cell level.

7. The method for measuring the number of cells applied to biological information according to claim 6, characterized in that: In step S3, the maximum cell aggregation amount of each cell level is determined according to the size measurement results. The specific steps are as follows: The ratio of the size to be assessed at each cell level to the size standard of suspended cells in the corresponding cell level is used as the cell amount assessment parameter of the corresponding cell level, and the cell amount assessment parameter of each cell level is rounded up as the maximum cell aggregation amount of the corresponding cell level.

8. The method for measuring the number of cells applied to biological information according to claim 7, characterized in that: In step S4, the suspension aggregation index of each cell layer is calculated by using a polynomial regression algorithm based on the layer density of each cell layer and the maximum cell aggregation amount. The specific steps are as follows: Normalized input: The Max-Min algorithm was used to normalize the cell layer density and the maximum cell aggregation; Constructing a polynomial regression formula: Constructing a polynomial regression formula based on the normalized results of the layer density of each cell layer and the maximum cell aggregation amount: , where a is the result of normalization of the layer density of each cell layer, b is the result of normalization of the maximum cell aggregation amount of each cell layer, c is the preset adjustment parameter, and F is the suspension aggregation index; The adjustment parameter c is used to control the numerical range of the suspension aggregation index.

9. The method for measuring the number of cells applied to biological information according to claim 8, characterized in that: In step S4, the suspension aggregation index of each cell level is converted into the measurement error value caused by the suspended cells using the conversion formula: , where C is the measurement error caused by the suspended cells in each culture dish, and s is the conversion ratio; The measurement error value caused by the suspended cells in each culture dish is compared with the preset error threshold. If the measurement error value caused by the suspended cells in the current culture dish exceeds the error threshold, the current culture dish is discarded and the cell number measurement is not performed; if the measurement error value caused by the suspended cells in the current culture dish is lower than the error threshold, the current culture dish is marked and the cell number measurement is performed.

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