Biological sample scheduling method and apparatus, storage medium, and program product

Abstract

The application provides a biological sample scheduling method and device, a storage medium and a program product. The method comprises the following steps: obtaining sample information of at least one scheduling unit; screening the sample information of the scheduling unit according to a preset priority standard to obtain a plurality of priority samples; combining and splitting the biological samples of the remaining scheduling units to obtain a plurality of second aggregation units, wherein the combining is used for combining the biological samples of the at least one scheduling unit remaining after the screening according to the preset priority standard, and the splitting is used for splitting the biological samples of the scheduling units remaining after the combining; and generating a scheduling list according to the sample information corresponding to the first aggregation units and the second aggregation units, the position layout of the biological samples of each first aggregation unit and each second aggregation unit on a well plate, the distribution information of the preset priority standard screening, the combining and the splitting. The application solves the problem of low distribution efficiency of biological samples in the prior art.

Description

Technical Field

[0001] This application relates to the field of bioinformatics, and more specifically, to a method for scheduling biological samples, a device for scheduling biological samples, a computer scale storage medium, and a computer program product. Background Technology

[0002] In the fields of bioscience research and clinical diagnostics, the management and scheduling of large quantities of biological samples (including but not limited to human, mouse, and cell samples) is a crucial task. With the surge in sample volume, the challenges faced by laboratories are constantly escalating, especially in the automation and intelligentization of storage, extraction, and testing processes. Current technologies primarily rely on device-level automation. Existing systems mainly focus on physical-level automation, lacking intelligent software scheduling algorithms for complex business rules. Existing systems typically rely on human experience for sample batching or employ simple rule engines, failing to dynamically optimize sample allocation and struggling to handle complex scheduling problems under multi-dimensional constraints. Particularly when dealing with scenarios such as human-mouse sample separation, pooled sample splitting, storage temperature matching, and prioritizing urgent samples, existing systems often require significant manual intervention, resulting in low efficiency and a high risk of errors. Summary of the Invention

[0003] The main objective of this application is to provide a biological sample scheduling method, a biological sample scheduling device, a computer scale storage medium, and a computer program product, so as to at least solve the problem of low allocation efficiency of biological samples in the prior art.

[0004] To achieve the above objectives, according to one aspect of this application, a method for scheduling biological samples is provided, comprising: acquiring sample information of at least one scheduling unit, wherein a scheduling unit includes a batch of biological samples, and the sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days; filtering the sample information of the scheduling unit according to a preset priority standard to obtain multiple priority samples, wherein the preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority, the preset conditions including a maximum sample quantity, extraction method, and remaining valid days, and the multiple priority samples form a first aggregation unit; and combining and splitting the biological samples of the remaining scheduling units to obtain... Multiple second aggregation units are defined, wherein "grouping" combines biological samples from at least one remaining scheduling unit after filtering according to a preset priority standard to form a second aggregation unit, and "splitting" splits the biological samples from the remaining scheduling units after grouping, and the split biological samples, together with the biological samples that did not form a second aggregation unit in the grouping, form a second aggregation unit. The number of biological samples in each second aggregation unit meets a preset range. A scheduling list is generated based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the position layout of the biological samples in each first aggregation unit on the well plate, the position layout of the biological samples in each second aggregation unit on the well plate, the preset priority standard filtering, and the allocation information of grouping and splitting.

[0005] Optionally, the scheduling method further includes: preprocessing the sample information of the scheduling unit, the preprocessing including checking the format of the sample information in the scheduling unit and removing sample information with incorrect format; and obtaining a standardized sample list of the scheduling unit based on the preprocessed sample information and the classification criteria, wherein the classification criteria are to classify the sample information according to species type, extraction method and sample type.

[0006] Optionally, the scheduling method further includes: after screening by a preset priority criterion, determining whether the combination of at least one remaining first target scheduling unit satisfies that the number of samples is within a preset range, wherein the first target scheduling unit is any one of the scheduling units; if the combination of at least one remaining first target scheduling unit satisfies that the number of samples is within the preset range, selecting first target scheduling units with the same storage temperature to form a second aggregation unit; if the combination of at least one remaining first target scheduling unit does not satisfy that the number of samples is within the preset range, splitting the biological samples of the second target scheduling unit into individual units, wherein the second target scheduling unit is a scheduling unit excluding the first target scheduling unit.

[0007] Optionally, the scheduling method further includes: if the number of biological samples in the second aggregation unit is less than the minimum value of a preset range, selecting a first target scheduling unit with a different storage temperature to supplement the second aggregation unit, so that the number of biological samples in the second aggregation unit is within the preset range.

[0008] Optionally, if it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within a preset interval, the biological samples of the second target scheduling unit are split into individual units, including: if it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within a preset interval, determining whether the total number of biological samples of the second target scheduling unit and the remaining first target scheduling units is greater than or equal to the maximum value of the preset interval; if the total number of biological samples is greater than or equal to the maximum value of the preset interval, sorting the second target scheduling units according to the number of biological samples from largest to smallest to obtain a first target sequence; and sequentially splitting the biological samples of the second target scheduling units of the first target sequence, with the split biological samples and the remaining first target scheduling units forming a second aggregation unit.

[0009] Optionally, the biological samples of the second target scheduling units of the first target sequence are split sequentially, including: when the number of biological samples of multiple second target scheduling units is the same and the biological samples of each second target scheduling unit have the same number of remaining valid days, the multiple second target scheduling units are sorted in ascending order according to the number of remaining valid days of the biological samples to obtain the second target sequence; and the biological samples of the second target scheduling units of the second target sequence are split sequentially.

[0010] Optionally, the biological samples of the second target scheduling units in the first target sequence are sequentially split, including: when the number of biological samples in multiple second target scheduling units is the same, and the biological samples of multiple second sub-target scheduling units in multiple second target scheduling units have multiple different remaining valid days, the biological samples of each second sub-target scheduling unit are classified according to the size of the remaining valid days to obtain a first category and a second category, wherein the remaining valid days of the first category are less than the remaining valid days of the second category; the multiple second sub-target scheduling units are arranged from largest to smallest according to the number of biological samples in the first category to obtain a third target sequence; and the biological samples of the second sub-target scheduling units in the third target sequence are sequentially split.

[0011] According to another aspect of this application, a biological sample scheduling device is provided, comprising: an acquisition module for acquiring sample information of at least one scheduling unit, wherein a scheduling unit includes a batch of biological samples, and the sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days; a first screening module for screening the sample information of the scheduling unit according to a preset priority standard to obtain multiple priority samples, wherein the preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority, the preset conditions including a maximum sample quantity, extraction method, and remaining valid days, and the multiple priority samples form a first aggregation unit; and a second screening module for combining and processing the biological samples of the remaining scheduling units. The process involves splitting orders to obtain multiple second aggregation units. "Order combining" combines biological samples from at least one remaining scheduling unit after filtering according to a preset priority standard to form a second aggregation unit. "Order splitting" further separates the biological samples from the remaining scheduling units after order combining. The split biological samples, along with those biological samples from order combining that did not form a second aggregation unit, form a second aggregation unit. The number of biological samples in each second aggregation unit satisfies a preset range. An integration module generates a scheduling list based on sample information corresponding to the first aggregation unit, sample information corresponding to the second aggregation unit, the positional layout of biological samples in each first aggregation unit on the well plate, the positional layout of biological samples in each second aggregation unit on the well plate, the preset priority standard filtering, and the allocation information for order combining and splitting.

[0012] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is running, a method for scheduling biological samples executed by the device where the computer-readable storage medium is located is provided.

[0013] According to another aspect of this application, a computer program product is provided, including computer instructions, which, when executed by a processor, implement a method for scheduling biological samples.

[0014] Applying the technical solution of this application, sample information of at least one scheduling unit is obtained. A scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days. The sample information of the scheduling unit is filtered according to a preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and these conditions have priority. The preset conditions include a maximum sample quantity, extraction method, and remaining valid days. Multiple priority samples form a first aggregation unit. The remaining biological samples from the scheduling units are combined and split into multiple second aggregation units. This system combines biological samples from at least one remaining scheduling unit after screening according to preset priority criteria to form a second aggregation unit. It also splits the remaining scheduling units after the initial order-combination process, and these split biological samples, along with those not included in the initial order-combination, form the second aggregation unit. The number of biological samples in each second aggregation unit meets a preset range. A scheduling list is generated based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the positional layout of the biological samples in each first aggregation unit on the well plate, the preset priority criteria screening, and the allocation information for order-combination and order-splitting. This application simultaneously considers multiple constraints such as sample quantity, species type, sample type, and extraction method to ensure that the scheduling results comply with laboratory standards. It can screen and classify data according to preset priority criteria. These criteria include maximizing the sample quantity, specific extraction methods (such as TRIzol), and samples nearing their expiration date, along with their priority ranking. The priority sample groups selected in this way constitute the first aggregation unit, ensuring that urgent samples and samples under specific conditions are processed promptly. For the remaining scheduling units, a strategy of combining and splitting orders is employed to generate multiple second aggregation units. Starting with high-priority samples, the process gradually transitions to ordinary samples, and finally, the remaining samples are processed through dynamic order splitting. This process is tightly coupled with experimental specifications, improving resource utilization. Finally, by comprehensively analyzing the sample information, well plate layout, and scheduling details of the first and second aggregation units, a detailed scheduling list is automatically generated, significantly improving the efficiency and accuracy of sample scheduling, reducing the need for manual intervention, and enhancing the standardization and traceability of laboratory operations. This solves the problem of low efficiency in biological sample allocation in existing technologies and provides strong support for the automation and intelligentization of biological laboratories. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a mobile terminal for executing a biological sample scheduling method according to an embodiment of this application is shown.

[0017] Figure 2 A flowchart illustrating a biological sample scheduling method according to an embodiment of this application is shown.

[0018] Figure 3 A structural block diagram of a biological sample scheduling device according to an embodiment of this application is shown;

[0019] The above figures include the following reference numerals:

[0020] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] As described in the background section, existing systems typically rely on human experience for sample batching or employ simple rule engines, making it impossible to dynamically optimize sample allocation and handle complex scheduling problems under multi-dimensional constraints. Especially in scenarios such as human-mouse sample separation, mixed sample allocation, storage temperature matching, and prioritizing urgent samples, existing systems often require significant manual intervention, resulting in low efficiency and a high risk of errors. To address the problem of low efficiency in biological sample allocation in existing technologies, embodiments of this application provide a biological sample scheduling method, a biological sample scheduling device, a computer-calibrated storage medium, and a computer program product.

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0026] The methods and embodiments provided in this application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a biological sample scheduling method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0027] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the biological sample scheduling method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0028] This embodiment provides a method for scheduling biological samples that runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] Figure 2 This is a flowchart of a biological sample scheduling method according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0030] Step S1: Obtain sample information for at least one scheduling unit. A scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days.

[0031] Specifically, it receives detailed information about one or more batches of biological samples, stored in structured electronic files (such as CSV or Excel). Each batch (scheduling unit) contains one or more biological samples, and the information entries include, but are not limited to, a unique sample identifier (sample number), sample quantity (number of samples per batch), species type (human, rodent, etc.), sample type (such as DNA or RNA samples), extraction method (such as TRIzol or CTAB extraction), preservation method (such as quick-freezing, FFPE, or PAXgene), storage temperature (specific temperature conditions, such as -80°C or -20°C), and remaining valid days (the remaining shelf life of the sample in its current state).

[0032] Step S2: The sample information of the scheduling unit is filtered according to the preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority. The preset conditions include the maximum number of samples, the extraction method, and the remaining valid days. The multiple priority samples form the first aggregation unit.

[0033] Specifically, priority criteria are set according to business needs, and typically include, but are not limited to: maximum sample size priority, samples extracted using a specific method (such as TRIzol) priority, and samples with the shortest remaining valid days priority. The priority among these three is: maximum sample size priority > TRIzol extraction priority > shortest remaining valid days priority. The samples with the highest priority are first grouped into the first aggregation unit to ensure these samples are processed preferentially. Multiple priority samples can form at least one first aggregation unit. For example, if six priority samples are selected, two priority sample combinations satisfy the preset conditions, the remaining three priority sample combinations satisfy the preset conditions, and one priority sample itself also satisfies the preset conditions, then three first aggregation units are generated.

[0034] Step S3: Combine and split the biological samples of the remaining scheduling units to obtain multiple second aggregation units. Combining is used to combine the biological samples of at least one scheduling unit that are still in the process of filtering by a preset priority standard to obtain a second aggregation unit. Splitting is used to split the biological samples of the remaining scheduling units after combining. The split biological samples and the biological samples that were not formed into a second aggregation unit in the combination are combined into a second aggregation unit. The number of biological samples in each second aggregation unit meets the preset range.

[0035] Specifically, after prioritizing sample processing, the remaining samples are intelligently grouped and split according to the plate capacity constraint (e.g., 96 wells). Grouping uses a subset sum algorithm to determine whether the remaining samples can be effectively combined into a single plate, aiming to approach but not exceed the maximum capacity (e.g., 96 wells) while not falling below the minimum effective capacity (e.g., 72 wells). If the minimum capacity requirement cannot be met, a dynamic splitting strategy is employed, polling from samples that do not meet the grouping conditions and selecting suitable samples to fill the unsuccessfully grouped wells, thus reaching the plate's maximum capacity. The intelligent grouping and splitting mechanism can dynamically adjust the scheduling strategy based on real-time sample status and laboratory needs without manual intervention. During grouping, at least one remaining scheduling unit after screening according to preset priority criteria can form at least one first aggregation unit. For example, if there are 5 remaining scheduling units, 2 of them satisfy the preset conditions, and the remaining 3 satisfy the preset conditions, thus generating 2 second aggregation units. When splitting orders, scheduling units that do not meet the criteria for combining orders are split. For example, if a scheduling unit after combining orders includes 60 biological samples, which does not meet the requirement of 72-96 samples, then 12-36 of these units will be split to make the total number of scheduling units 72-96. The specific number of splits needs to be determined based on the actual situation. For example, if the scheduling unit to be split includes 112 samples, it can be split into 12-40 units; if the scheduling unit to be split includes 80 samples, it can be split into 8 units.

[0036] Step S4: Generate a scheduling list based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the position layout of the biological samples of each first aggregation unit on the well plate, the position layout of the biological samples of each second aggregation unit on the well plate, the preset priority standard screening, and the allocation information for combining and splitting orders.

[0037] Specifically, the sample information from the first and second aggregation units is summarized, along with information such as the layout of each unit on the well plate and sample allocation details, to generate a detailed scheduling list and a structured scheduling file for easy reference and execution by laboratory technicians. The sample information corresponding to the first and second aggregation units includes various sample information for the biological samples in that unit; the location of each biological sample on the well plate; and the allocation information for preset priority criteria screening, order combining, and order splitting, including: which biological samples were scheduled from which scheduling units during the process of obtaining the aggregation unit, and the overall scheduling path.

[0038] The scheduling method in this embodiment can simultaneously consider multiple constraints such as sample quantity, species type, sample type, and extraction method to ensure that the scheduling results comply with laboratory standards. It can filter and classify data according to preset priority criteria. These criteria include maximizing the sample quantity, specific extraction methods (such as TRIzol), and samples nearing their expiration date, along with their priority ranking. The selected priority sample groups constitute the first aggregation unit, ensuring timely processing of urgent samples and samples under specific conditions. For the remaining scheduling units, a strategy of combining and splitting orders is employed to generate multiple second aggregation units. Processing begins with high-priority samples, gradually transitioning to ordinary samples, and finally, the remaining samples are processed through dynamic order splitting. This process is tightly coupled with experimental standards, improving resource utilization. Finally, by comprehensively analyzing the sample information, well plate layout, and scheduling details of the first and second aggregation units, a detailed scheduling list is automatically generated, significantly improving the efficiency and accuracy of sample scheduling, reducing the need for manual intervention, and enhancing the standardization and traceability of laboratory operations. This solves the problem of low efficiency in biological sample allocation in existing technologies and provides strong support for the automation and intelligence of biological laboratories.

[0039] In the specific implementation process, the following additional steps are included between steps S1 and S2:

[0040] The sample information of the scheduling unit undergoes preprocessing. This preprocessing includes checking the format of the sample information in the scheduling unit and removing samples with incorrect formats. Before formal scheduling, all received sample information undergoes preprocessing steps to ensure data accuracy and usability. This process mainly includes format checks on data fields in electronic files (such as CSV files), such as verifying whether the sample number is unique, whether the species type is a predefined option (human, mouse, other), and whether the storage temperature meets the scientific range for biological sample preservation. If sample entries with incorrect data formats or missing key information are found, these entries will be automatically removed to prevent erroneous data from interfering with subsequent scheduling algorithms.

[0041] Based on the preprocessed sample information and classification criteria, a standardized sample list for the scheduling unit is obtained. The classification criteria are based on species type, extraction method, and sample type. After data preprocessing, the sample information is further organized according to the preset classification criteria. These criteria include, but are not limited to, species type (e.g., human, rodent), extraction method (e.g., TRIzol, CTAB), and sample type (e.g., DNA, RNA). Classifying the sample information according to these criteria generates a standardized sample list, ensuring consistency within each category and facilitating subsequent batch processing and operations. By judging the species distribution before scheduling or verifying the well position status during scheduling, it is ensured that only a single species sample is contained within the same well plate, effectively handling the complex business rule of humans and rodents not sharing plates.

[0042] In the process of combining orders, the scheduling methods also include:

[0043] After screening according to preset priority criteria, it is determined whether the combination of at least one remaining first target scheduling unit satisfies the requirement that the number of samples is within a preset range. The first target scheduling unit can be any one of the scheduling units. After processing the priority samples and generating at least one first aggregation unit, the unassigned first target scheduling units are evaluated to check whether the number of samples when any one or two are combined is within a preset range (e.g., the minimum effective capacity of the orifice plate is 72 or the maximum capacity is 96). If the current combination meets the range requirement, that is, the total number of samples falls between the preset minimum and maximum number of orifices, the first target scheduling units in the current combination can be combined to form a second aggregation unit.

[0044] If the number of samples from at least one remaining combination of first target scheduling units falls within a preset range, then first target scheduling units with the same storage temperature are selected to form a second aggregation unit. Once the number of samples from the remaining combinations of first target scheduling units meets the preset range, further screening is performed, prioritizing the selection of first target scheduling units with the same storage temperature to form the second aggregation unit. This operation ensures that samples requiring the same processing conditions can be processed together, avoiding sample damage or experimental failure due to mismatched processing conditions.

[0045] If it is determined that the number of samples in at least one of the remaining first target scheduling units does not meet the preset range, the biological samples of the second target scheduling unit will be split into batches. The second target scheduling unit is any scheduling unit other than the first target scheduling unit. If the number of samples in the remaining first target scheduling unit combinations exceeds the preset range limit (i.e., the total number of samples exceeds the maximum number of wells or is lower than the minimum number of valid wells), a batch splitting strategy will be adopted. A portion of the samples will be split from the second target scheduling unit with the largest number of samples that has not yet been combined into batches (or scheduling units that do not meet the batch combining requirements) to reach the preset range of sample numbers and meet the requirements of the next step of processing. The split samples will be recombined with other scheduling units that have not met the requirements to form a new batch.

[0046] Following the step of selecting first target scheduling units with the same storage temperature to form a second aggregation unit when the combination of at least one remaining first target scheduling unit satisfies the condition that the number of samples is within a preset range, in some optional embodiments, if the number of biological samples appearing in the formed second aggregation unit is less than the minimum value of the preset range, first target scheduling units with different storage temperatures are selected to supplement the second aggregation unit so that the number of biological samples in the second aggregation unit is within the preset range. When it is found during the batching process that even combining all samples with the same storage temperature cannot meet the minimum sample number requirement of the preset range, the conditions are relaxed to allow mixing samples with different storage temperatures to supplement the minimum sample number required to meet the preset range. This operation, while ensuring a sufficient number of samples, takes into account the issue of storage temperature compatibility and avoids processing delays caused by insufficient numbers of a single sample category.

[0047] The above-mentioned step of splitting the biological samples of the second target scheduling unit when it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the sample number is within a preset range includes:

[0048] If the combination of at least one remaining first target scheduling unit does not satisfy the requirement that the sample number falls within a preset interval, then it is determined whether the total number of biological samples from the second target scheduling unit and the remaining first target scheduling units is greater than or equal to the maximum value of the preset interval. Since the current method of combining first target scheduling units by grouping samples cannot meet the requirements of the preset interval, the total number of samples from all remaining scheduling units (including the first and second target scheduling units that failed to group samples) is statistically analyzed. If this total number of samples meets the preset interval, it indicates that all remaining scheduling units can still form a complete aggregation unit. This check involves summarizing the sample numbers of all unassigned scheduling units and comparing whether the total number of samples after summarization reaches the preset maximum number of wells.

[0049] If the total number of biological samples is greater than or equal to the maximum value of a preset interval, the second target scheduling units are sorted in descending order of the number of biological samples to obtain the first target sequence. If the total number of samples in the remaining scheduling units can reach the upper limit of the preset interval (maximum number of wells), the second target scheduling units are sorted in descending order of the number of samples to form the first target sequence. This sequence is used for subsequent order splitting operations, allowing the scheduling unit with the largest number of samples to participate in the splitting first. This can maximize the capacity of the currently combined units and maximize the probability that the split scheduling units meet the preset interval, thus simplifying the scheduling process to some extent.

[0050] The biological samples of the second target scheduling units in the first target sequence are sequentially split. The split biological samples, together with the remaining first target scheduling units, form a second aggregation unit. Following the first target sequence, starting with the second target scheduling unit with the largest number of samples, the biological samples within it are split and combined into the current batch until the maximum number of wells is reached. The splitting process is dynamically adjusted to ensure that the number of samples split each time exactly reaches the upper limit of the preset interval (prioritizing maximizing the number of samples in the resulting aggregation unit). Simultaneously, the remaining samples of the split second target scheduling units are retained to continue participating in the combination in subsequent scheduling stages, forming new second aggregation units (if the remaining samples of a split second target scheduling unit exactly meet the upper limit of the preset interval, the next second target scheduling unit for that sample can be split).

[0051] In some optional implementations, the biological samples of the second target scheduling unit of the first target sequence are sequentially split, including:

[0052] When multiple second-target scheduling units have the same number of biological samples and each unit has the same number of remaining valid days, the units are sorted in ascending order of the remaining valid days to obtain a second-target sequence. When two or more second-target scheduling units have exactly the same number of samples and all biological samples within each unit have the same number of remaining valid days, these units are sorted in ascending order of the remaining valid days to generate a second-target sequence. This sorting takes into account the urgency of the samples, prioritizing samples with fewer remaining days to ensure the priority of samples nearing expiration.

[0053] The biological samples in the second target scheduling unit of the second target sequence are split sequentially. The biological samples in the second target scheduling unit are split one by one according to the generated second target sequence, which is a sequence arranged in ascending order of remaining valid days. The split samples are then added to the currently constructed batch until the maximum capacity limit is reached (the splitting strategy described above can be the same). This splitting process considers the timeliness and quantity of the samples, ensuring that each batch fully utilizes resources while prioritizing biological materials with closer expiration dates.

[0054] In some optional implementations, the biological samples of the second target scheduling unit of the first target sequence are sequentially split, including:

[0055] When multiple second-target scheduling units have the same number of biological samples, and multiple second-sub-target scheduling units within these units have different remaining valid days, the biological samples in each second-sub-target scheduling unit are classified according to the remaining valid days, resulting in a first category and a second category. The remaining valid days in the first category are less than those in the second category. When the number of samples is the same, but multiple second-target scheduling units have inconsistent remaining valid days, the samples in these second-sub-target scheduling units are classified according to the remaining valid days, resulting in a first category with shorter remaining days and a second category with longer remaining days (if there are more than two types of remaining valid days, there can be a third category, a fourth category, etc., with the remaining valid days in the first to fourth categories gradually increasing). This classification process emphasizes consideration of resource validity. By prioritizing the classification of samples nearing expiration, the system can ensure that they are processed in a timely manner, avoiding resource waste.

[0056] Multiple second-sub-target scheduling units are arranged in descending order of the number of biological samples in the first category to obtain the third-target sequence. Then, based on the number of samples in the first category (i.e., samples with shorter remaining valid days), multiple second-sub-target scheduling units are reordered to form the third-target sequence. This ordering ensures that the system prioritizes samples with urgency; that is, samples with short remaining valid days and urgent processing needs to be given priority to supplement the current batch of samples, ensuring the effective utilization of experimental resources.

[0057] The biological samples of the second sub-target scheduling unit of the third target sequence are split sequentially. Based on the third target sequence (sorted by the shortest remaining valid days and sample size from largest to smallest), each second sub-target scheduling unit is split to replenish the current batch to the preset maximum sample size. During this splitting process, the system dynamically adjusts to ensure that the number of samples split each time exactly reaches the maximum effective capacity of the current batch, while retaining the remaining samples after splitting to continue participating in subsequent scheduling stages, forming new aggregation units for processing. If there are more than two types of remaining valid days, such as a first, second, and third category, the first category (the one with the fewest days) is sorted first (the third target sequence), and splitting is performed according to this sorting, prioritizing the splitting of samples with the first category. After all samples with the first category in all second target scheduling units have been split, the samples with the second category are now the samples with the fewest days (equivalent to the first category in the previous step). They are then sorted according to the second category (equivalent to updating the third target sequence obtained in the previous step), and the samples with the second category are split according to this sorting, and so on.

[0058] In the above steps, high-priority samples are processed into individual orders, orders are combined using a greedy algorithm, large batches are split into smaller orders, and expired samples are forcibly allocated. This process is tightly coupled with experimental specifications (such as human-mouse separation and independent handling of special storage methods) to ensure that the scheduling results can be directly used for experimental execution. The batch generation logic adopts a modular and layered design, with core scheduling steps (such as individual order processing, order combination, and order splitting) implemented as independent sub-processes, reserving structural space for the future introduction of more complex optimization algorithms (such as integer programming and metaheuristic search).

[0059] Furthermore, the AutoDispatch software used to execute the above methods can provide command-line interface and configuration file support, allowing users to specify input paths, output formats, priority weights, board types, etc. through parameters.

[0060] The aforementioned AutoDispatch software can also manage the status of well plates based on bitmaps, efficiently recording the occupancy status, sample type, and species information of each well. While ensuring human-mouse separation and mixed sample rules, it achieves O(1) level well query and update. Specifically, it uses a 96-bit bitmap to represent the occupancy status (1 = occupied, 0 = idle), and uses two other dictionaries to store the sample type ID and species ID of each well, respectively. The dictionaries are indexed by well position (0-95). O(1) query and update can be achieved. Part of the code is as follows:

[0061] 1. Check if a hole is free: if(bitmap>>pos)&1==0 (one right shift and bitwise AND operation);

[0062] 2. Mark a certain well as occupied: bitmap |= (1 << pos) (a single bitwise OR operation);

[0063] 3. Record species information: species[pos] = 'human' (a single array assignment);

[0064] 4. Separate human and mouse samples: Maintain two 96-bit masks, human_bitmap and mouse_bitmap, for each plate. Before allocating a new sample, if it is a "human" sample, only need to check if mouse_bitmap!= 0.

[0065] The following introduces the scheduling device for biological samples provided by the embodiments of the present application.

[0066] Figure 3 It is a schematic diagram of the scheduling device for biological samples according to the embodiments of the present application. As Figure 3 shown, the device includes: an acquisition module 10 for acquiring sample information of at least one scheduling unit, where a scheduling unit includes a batch of biological samples, and the sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days; a first screening module 20 for screening the sample information of the scheduling unit according to a preset priority standard to obtain multiple priority samples, the preset priority standard includes multiple preset conditions, and the multiple preset conditions have priorities, the preset conditions include the sample quantity being the maximum value, extraction method, and remaining valid days, and the multiple priority samples form a first aggregation unit; a second screening module 30 for combining and splitting the remaining biological samples of the scheduling unit to obtain multiple second aggregation units, where combining is used to combine the biological samples of at least one scheduling unit remaining after being screened by the preset priority standard to obtain a second aggregation unit, and splitting is used to split the biological samples of the scheduling unit remaining after combining, and the split biological samples and the biological samples that did not form a second aggregation unit during combining form a second aggregation unit, and the quantity of biological samples in each second aggregation unit satisfies a preset interval; an integration module 40 for generating a scheduling list according to the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the position layout of the biological samples in each first aggregation unit on the microplate, the position layout of the biological samples in each second aggregation unit on the microplate, the allocation information of the preset priority standard screening, combining, and splitting.

[0067] As an optional solution, the scheduling device also includes a processing module and a first determining module. The processing module is used to preprocess the sample information of the scheduling unit. The preprocessing includes checking the format of the sample information in the scheduling unit and removing sample information with incorrect format. The first determining module is used to obtain a standardized sample list of the scheduling unit based on the preprocessed sample information and the classification criteria. The classification criteria are to classify the sample information according to species type, extraction method and sample type.

[0068] In one optional scheme, the scheduling device further includes a first judgment module, a first aggregation module, and a first splitting module. The first judgment module, after screening according to a preset priority standard, determines whether the combination of at least one remaining first target scheduling unit satisfies the requirement that the sample quantity is within a preset range. The first target scheduling unit is any one of the scheduling units. The first aggregation module, if it determines that the combination of at least one remaining first target scheduling unit satisfies the requirement that the sample quantity is within the preset range, selects first target scheduling units with the same storage temperature to form a second aggregation unit. The first splitting module, if it determines that the combination of at least one remaining first target scheduling unit does not satisfy the requirement that the sample quantity is within the preset range, splits the biological samples of the second target scheduling unit into separate orders. The second target scheduling unit is any scheduling unit other than the first target scheduling unit.

[0069] In one optional scheme, the scheduling device further includes a second order splitting module, which is used to select a first target scheduling unit with a different storage temperature to supplement the second aggregation unit when the number of biological samples in the second aggregation unit is less than the minimum value of a preset range, so that the number of biological samples in the second aggregation unit is within the preset range.

[0070] In one optional scheme, the first splitting module includes a first sub-judgment module, a first sub-sorting module, and a first sub-splitting module. The first sub-judgment module is used to determine whether the total number of biological samples of the second target scheduling unit and the remaining first target scheduling units is greater than or equal to the maximum value of the preset interval if the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within a preset interval. The first sub-sorting module is used to sort the second target scheduling units according to the number of biological samples from largest to smallest if the total number of biological samples is greater than or equal to the maximum value of the preset interval, thus obtaining a first target sequence. The first sub-splitting module is used to sequentially split the biological samples of the second target scheduling units in the first target sequence, and the split biological samples, together with the remaining first target scheduling units, form a second aggregation unit.

[0071] In one optional scheme, the first sub-splitting module includes a first sub-sorting unit and a first sub-splitting unit. The first sub-sorting unit is used to sort the multiple second target scheduling units in ascending order of the remaining valid days of their biological samples when the number of biological samples in the multiple second target scheduling units is the same and the biological samples in each second target scheduling unit have the same number of remaining valid days, thereby obtaining a second target sequence. The first sub-splitting unit is used to split the biological samples of the second target scheduling units in the second target sequence in sequence.

[0072] In one optional scheme, the first sub-splitting module further includes a first sub-classification unit, a second sub-sorting unit, and a second sub-splitting unit. The first sub-classification unit is used to classify the biological samples of each second sub-target scheduling unit according to the remaining valid days when the number of biological samples in multiple second target scheduling units is the same, and the biological samples in multiple second sub-target scheduling units have multiple different remaining valid days. This results in a first category and a second category, where the remaining valid days in the first category are less than those in the second category. The second sub-sorting unit is used to arrange the multiple second sub-target scheduling units in descending order of the number of biological samples in the first category, resulting in a third target sequence. The second sub-splitting unit is used to sequentially split the biological samples of the second sub-target scheduling units in the third target sequence.

[0073] The biological sample scheduling device includes a processor and a memory. The aforementioned acquisition modules are all stored as program modules in the memory, and the processor executes the program units stored in the memory to achieve the corresponding functions. All of the aforementioned modules reside in the same processor; alternatively, the modules may be located in different processors in any combination.

[0074] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters can address the low efficiency of biological sample allocation in existing technologies.

[0075] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0076] This invention provides a computer-readable storage medium including a stored program, wherein the program, when running, controls the device where the computer-readable storage medium is located to execute a biological sample scheduling method.

[0077] Specifically, methods for scheduling biological samples include:

[0078] Step S1: Obtain sample information for at least one scheduling unit. A scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days.

[0079] Step S2: The sample information of the scheduling unit is filtered according to the preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority. The preset conditions include the maximum number of samples, the extraction method, and the remaining valid days. The multiple priority samples form the first aggregation unit.

[0080] Step S3: Combine and split the biological samples of the remaining scheduling units to obtain multiple second aggregation units. Combining is used to combine the biological samples of at least one scheduling unit that are still in the process of filtering by a preset priority standard to obtain a second aggregation unit. Splitting is used to split the biological samples of the remaining scheduling units after combining. The split biological samples and the biological samples that were not formed into a second aggregation unit in the combination are combined into a second aggregation unit. The number of biological samples in each second aggregation unit meets the preset range.

[0081] Step S4: Generate a scheduling list based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the position layout of the biological samples of each first aggregation unit on the well plate, the position layout of the biological samples of each second aggregation unit on the well plate, the preset priority standard screening, and the allocation information for combining and splitting orders.

[0082] This invention provides a processor for running a program, wherein the program executes a biological sample scheduling method during runtime.

[0083] Specifically, methods for scheduling biological samples include:

[0084] Step S1: Obtain sample information for at least one scheduling unit. A scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days.

[0085] Step S2: The sample information of the scheduling unit is filtered according to the preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority. The preset conditions include the maximum number of samples, the extraction method, and the remaining valid days. The multiple priority samples form the first aggregation unit.

[0086] Step S3: Combine and split the biological samples of the remaining scheduling units to obtain multiple second aggregation units. Combining is used to combine the biological samples of at least one scheduling unit that are still in the process of filtering by a preset priority standard to obtain a second aggregation unit. Splitting is used to split the biological samples of the remaining scheduling units after combining. The split biological samples and the biological samples that were not formed into a second aggregation unit in the combination are combined into a second aggregation unit. The number of biological samples in each second aggregation unit meets the preset range.

[0087] Step S4: Generate a scheduling list based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the position layout of the biological samples of each first aggregation unit on the well plate, the position layout of the biological samples of each second aggregation unit on the well plate, the preset priority standard screening, and the allocation information for combining and splitting orders.

[0088] This invention provides a device including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps: acquiring sample information from at least one scheduling unit, where each scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days; filtering the sample information from the scheduling unit according to a preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and these preset conditions have priority. The preset conditions include a maximum sample quantity, extraction method, and remaining valid days. The multiple priority samples form a first aggregation unit; and the remaining biological samples from the scheduling units are then processed. Biological samples are combined and split into multiple second aggregation units. Combining samples from at least one remaining scheduling unit after filtering according to a preset priority standard results in a second aggregation unit. Splitting samples from the remaining scheduling units after combining samples further splits them into individual second aggregation units. These split samples, along with biological samples from the combining process that did not form a second aggregation unit, are then combined into a second aggregation unit. The number of biological samples in each second aggregation unit meets a preset range. A scheduling list is generated based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the positional layout of the biological samples in each first aggregation unit on the well plate, the preset priority standard filtering, and the allocation information for combining and splitting samples. The devices mentioned in this paper can be servers, PCs, tablets, mobile phones, etc.

[0089] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps: acquiring sample information of at least one scheduling unit, wherein a scheduling unit includes a batch of biological samples, and the sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining valid days; filtering the sample information of the scheduling unit according to a preset priority standard to obtain multiple priority samples, wherein the preset priority standard includes multiple preset conditions, and the multiple preset conditions have priority, the preset conditions including a maximum sample quantity, extraction method, and remaining valid days, and the multiple priority samples form a first aggregation unit; and combining the biological samples of the remaining scheduling units into a single batch. The process involves combining and splitting orders to obtain multiple second aggregation units. The first aggregation unit combines biological samples from at least one remaining scheduling unit after filtering according to a preset priority standard. The second aggregation unit splits the biological samples from the remaining scheduling units after combining orders. The split biological samples, along with those biological samples from combining orders that did not form a second aggregation unit, form a second aggregation unit. The number of biological samples in each second aggregation unit satisfies a preset range. A scheduling list is generated based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the positional layout of the biological samples in each first aggregation unit on the well plate, the preset priority standard filtering, and the allocation information for combining and splitting orders.

[0090] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0091] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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, etc.) containing computer-usable program code.

[0092] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0096] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0097] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0098] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0099] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0100] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0101] 1) The biological sample scheduling method of this application can simultaneously consider multiple constraints such as sample quantity, species type, sample type, and extraction method to ensure that the scheduling results comply with laboratory standards. It can screen and classify data according to preset priority criteria. These criteria include maximizing the sample quantity, specific extraction methods (such as TRIzol), and samples nearing their expiration date, along with their priority ranking. The selected priority sample groups constitute the first aggregation unit, ensuring timely processing of urgent samples and samples under specific conditions. For the remaining scheduling units, a strategy of combining and splitting orders is employed to generate multiple second aggregation units. Processing begins with high-priority samples, gradually transitioning to ordinary samples, and finally, the remaining samples are processed through dynamic order splitting. This process is tightly coupled with experimental standards, improving resource utilization. Finally, by comprehensively analyzing the sample information, well plate layout, and scheduling details of the first and second aggregation units, a detailed scheduling list is automatically generated, significantly improving the efficiency and accuracy of sample scheduling, reducing the need for manual intervention, and enhancing the standardization and traceability of laboratory operations. This solves the problem of low efficiency in biological sample allocation in existing technologies and provides strong support for the automation and intelligence of biological laboratories.

[0102] 2) The biological sample scheduling method of this application ensures that only a single species sample is contained in the same well plate by judging the species distribution before scheduling or verifying the well position status during scheduling, effectively handling the complex business rule that humans and mice cannot share plates; using the above scheduling method, the scheduling task is shortened from an average of 2-3 hours for samples to 10-15 minutes. Manual intervention is reduced by 90%, and scheduling personnel only need to intervene in a very few special cases.

[0103] 3) Compared with systems such as Beckman Coulter AutoMate 2550, the biological sample scheduling method of this application mainly focuses on physical-level automation and has a high degree of intelligence. It can autonomously decide on sample batching strategies; it can simultaneously handle multiple complex business rules such as human-mouse non-co-plating, storage temperature matching, and priority for urgent samples, demonstrating strong rule processing capabilities; it can dynamically adjust scheduling strategies based on real-time sample status and laboratory needs, making it more adaptable; and it automatically records the scheduling decision process and results by recording scheduling lists, facilitating quality control and problem investigation, and improving laboratory management.

[0104] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for scheduling biological samples, characterized in that, include: The effective capacity of the well plate containing biological samples and sample information of at least one scheduling unit are obtained. Each scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature, and remaining effective days. The sample information of the scheduling unit is filtered according to a preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and the multiple preset conditions have priorities. The preset conditions include the maximum number of samples, the extraction method, and the remaining valid days. The priorities of the multiple preset conditions from high to low are: the maximum number of samples, the extraction method, and the remaining valid days. The multiple priority samples form a first aggregation unit. The remaining biological samples from the scheduling units are combined and split according to the storage temperature, the effective capacity of the well plate, and the remaining effective days to obtain multiple second aggregation units. The combination is used to combine the biological samples of at least one scheduling unit that are still remaining after being filtered by the preset priority criteria to obtain a second aggregation unit. The splitting is used to split the biological samples of the scheduling units that are still remaining after the combination. The split biological samples are combined with the biological samples that were not formed into the second aggregation unit in the combination to form the second aggregation unit. The number of biological samples in each second aggregation unit meets a preset range. A scheduling list is generated based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the positional layout of the biological samples of each first aggregation unit on the well plate, the positional layout of the biological samples of each second aggregation unit on the well plate, the preset priority standard screening, and the allocation information for combining orders and splitting orders.

2. The scheduling method according to claim 1, characterized in that, The scheduling method further includes: The sample information of the scheduling unit is preprocessed, and the preprocessing includes checking the format of the sample information in the scheduling unit and removing sample information with incorrect format. Based on the preprocessed sample information and classification criteria, a standardized sample list for the scheduling unit is obtained. The classification criteria are used to classify the sample information according to the species type, the extraction method, and the sample type.

3. The scheduling method according to claim 1, characterized in that, The scheduling method further includes: After filtering by the preset priority criteria, it is determined whether the combination of at least one remaining first target scheduling unit satisfies the condition that the number of samples is within the preset range, where the first target scheduling unit is any one of the scheduling units; If it is determined that the combination of at least one remaining first target scheduling unit satisfies the condition that the number of samples is within the preset range, then the first target scheduling units with the same storage temperature are selected to form the second aggregation unit. If it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within the preset range, the biological samples of the second target scheduling unit are split into two groups, where the second target scheduling unit is the scheduling unit other than the first target scheduling unit.

4. The scheduling method according to claim 3, characterized in that, The scheduling method further includes: If the number of biological samples in the second aggregation unit is less than the minimum value of the preset range, the first target scheduling unit with a different storage temperature is selected and added to the second aggregation unit so that the number of biological samples in the second aggregation unit is within the preset range.

5. The scheduling method according to claim 3, characterized in that, The step of splitting the biological samples of the second target scheduling unit when it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within the preset range includes: If it is determined that the combination of at least one remaining first target scheduling unit does not satisfy the condition that the number of samples is within the preset interval, then it is determined whether the total number of biological samples of the second target scheduling unit and the remaining first target scheduling unit is greater than or equal to the maximum value of the preset interval. If the total number of biological samples is greater than or equal to the maximum value of the preset interval, the second target scheduling unit is sorted from largest to smallest according to the number of biological samples to obtain the first target sequence; The biological samples of the second target scheduling unit of the first target sequence are split sequentially, and the split biological samples and the remaining first target scheduling units form the second aggregation unit.

6. The scheduling method according to claim 5, characterized in that, The step of sequentially splitting the biological samples of the second target scheduling unit of the first target sequence includes: When the number of biological samples in multiple second target scheduling units is the same, and the biological samples in each second target scheduling unit have the same number of remaining valid days, the multiple second target scheduling units are sorted in ascending order according to the number of remaining valid days of the biological samples to obtain a second target sequence. The biological samples of the second target scheduling unit of the second target sequence are split sequentially.

7. The scheduling method according to claim 5, characterized in that, The step of sequentially splitting the biological samples of the second target scheduling unit of the first target sequence includes: When the number of biological samples in multiple second target scheduling units is the same, and the biological samples in multiple second sub-target scheduling units in multiple second target scheduling units have multiple different remaining valid days, the biological samples in each second sub-target scheduling unit are classified according to the size of the remaining valid days to obtain a first category and a second category, wherein the remaining valid days of the first category are less than the remaining valid days of the second category. The multiple second sub-target scheduling units are arranged from largest to smallest according to the number of biological samples in the first category to obtain the third target sequence; The biological samples of the second sub-target scheduling unit of the third target sequence are split sequentially.

8. A biological sample scheduling device, characterized in that, include: An acquisition module is used to acquire the effective capacity of the well plate on which biological samples are placed and the sample information of at least one scheduling unit. One scheduling unit includes a batch of biological samples. The sample information includes sample number, sample quantity, species type, sample type, extraction method, preservation method, storage temperature and remaining effective days. The first filtering module is used to filter the sample information of the scheduling unit according to a preset priority standard to obtain multiple priority samples. The preset priority standard includes multiple preset conditions, and the multiple preset conditions have priorities. The preset conditions include the maximum number of samples, the extraction method, and the remaining valid days. The priorities of the multiple preset conditions from high to low are: the maximum number of samples, the extraction method, and the remaining valid days. The multiple priority samples form a first aggregation unit. The second screening module is used to combine and split the remaining biological samples of the scheduling units according to the storage temperature, the effective capacity of the well plate, and the remaining effective days to obtain multiple second aggregation units. The combination is used to combine the biological samples of at least one scheduling unit remaining after screening by the preset priority standard to obtain a second aggregation unit. The splitting is used to split the biological samples of the scheduling units remaining after the combination. The split biological samples and the biological samples that did not form a second aggregation unit in the combination are combined to form a second aggregation unit. The number of biological samples in each second aggregation unit meets a preset range. The integration module is used to generate a scheduling list based on the sample information corresponding to the first aggregation unit, the sample information corresponding to the second aggregation unit, the positional layout of the biological samples of each first aggregation unit on the well plate, the positional layout of the biological samples of each second aggregation unit on the well plate, the preset priority standard screening, and the allocation information of order combining and order splitting.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the biological sample scheduling method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the biological sample scheduling method according to any one of claims 1 to 7.

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