53 results about "Genetic Evolution" patented technology

The invention discloses a D / Yama2019 genetic evolution pedigree influenza delta virus reverse genetic operating system. According to the invention, DNA fragments corresponding to segments of PB2, PB1, P3, HEF, NP, M and NS of a full-length genome of D / JY3002 are amplified by using seven pairs of designed primers, the DNA fragments are seamlessly cloned to a pHW2000 vector and a pCC1-DualPro vector to construct plasmids, the plasmids are co-transfected to a cell line, and the artificially rescued D / Yama2019 genetic evolution pedigree influenza delta virus rD / JY3002 is obtained; the genomic sequence of the rD / JY3002 is completely consistent with the genomic sequence of a naturally separated strain D / JY3002, the infection ability is equivalent, and the rD / JY3002 can be stably subcultured for at least five generations. According to the present invention, the constructed unidirectional expression plasmid pPolI-D / JY3002-PB1-240-GFP-240 is adopted to obtain the artificially rescued recombinant influenza delta virus rD / JY3002-GFP carrying the green fluorescence reporter gene, and after the host cell is infected, the GFP expression quantity is high and stable; the invention establishes an efficient and stable D / Yama2019 genetic evolution pedigree influenza delta virus reverse genetic operating system which can be used for developing an influenza delta virus vector presenting exogenous gene.

The invention discloses a chip for genome breeding and variety identification of tilapia mossambica. The invention provides a group of SNP (Single Nucleotide Polymorphism) marker combination for tilapia mossambica, which comprises 50000 SNP markers which are respectively SNP1-SNP50000 markers. According to the invention, the SNP marker combination related to economic characters of tilapia mossambica is integrated, representative sites with uniform coverage are selected, a biological probe for site typing is developed, and the site coverage, typing accuracy and GS accuracy of the SNP marker combination are basically consistent with those of re-sequencing; the method can be applied to the aspects of tilapia germplasm resource identification, genetic relationship identification, SNP typing, variety identification, molecular breeding, DNA fingerprint database construction, variety purity detection, germplasm resource genetic analysis, whole genome selective breeding, functional gene positioning, genetic map construction, genetic evolution analysis, whole genome association analysis and the like.

The invention relates to the technical field of agricultural disease control, in particular to a core microbiome for strongly controlling cucumber fusarium wilt as well as a preparation method and application of the core microbiome. According to the invention, three biocontrol bacteria with high antagonistic ability to fusarium oxysporum of cucumber are screened from rhizosphere soil of cucumber, and the three biocontrol bacteria are respectively bacillus velezensis VJH5041, paenibacillus polymyxa SXC20-B62 and bacillus subtilis YJZL20-1 through whole genome sequencing and genetic evolution analysis; however, it is found that the strain is significantly different from the reported strain in the aspects of genomic sequence and function, and it is detected that the three strains are not reported, and microbial strain preservation is completed. Meanwhile, culture conditions and proportions of mixed fermentation of core microorganisms of the three biocontrol strains are optimally designed, so that a better culture effect is achieved. Through condition optimization, the core microbiome has a remarkable biocontrol effect on cucumber fusarium wilt, the biocontrol effect of the core microbiome is obviously higher than that of a single strain, and the core microbiome can remarkably promote growth of cucumber seedlings.

The invention provides an SNP (Single Nucleotide Polymorphism) molecular marker primer combination for molecular identification of soft fiber areca seed resources and application of the SNP molecular marker primer combination, and belongs to the technical field of SNP molecular markers. Genetic background correlation analysis of fruit fiber phenotypic characteristics is carried out based on constructed areca seed core germplasm resources, SNP molecular marker primers are developed according to areca seed fiber specific sites, and the SNP molecular marker primer development comprises four pairs of specific primers; the invention also provides a method for detecting the germplasm resource of the areca catechu by using the SNP molecular marker primer. The method can be used for rapidly and accurately detecting the genotype of the germplasm resource of the areca catechu at low cost and high throughput. The four pairs of specific primers can be used for identifying the germplasm resources of the soft-fiber areca catechu, and have important application significance on scientifically protecting the diversity of the germplasm resources of the areca catechu, researching genetic protection and genetic evolution of the areca catechu resources and genetic breeding of the areca catechu.

This invention provides a combination of SNP molecular marker primers for the molecular identification of soft-fiber areca nut germplasm resources and their applications, belonging to the field of SNP molecular marker technology. Based on the constructed core areca nut germplasm resources, this invention conducts genetic background association analysis on the phenotypic characteristics of fruit fibers and develops SNP molecular marker primers based on areca nut fiber-specific loci. The development of these SNP molecular marker primers includes four pairs of specific primers. This invention also provides a method for detecting soft-fiber areca nut germplasm resources using SNP molecular marker primers. This method can rapidly, accurately, cost-effectively, and with high throughput detect the genotype of soft-fiber areca nut germplasm resources. The four pairs of specific primers of this invention can be used to identify soft-fiber areca nut germplasm resources, which has important application significance for the scientific protection of areca nut germplasm resource diversity, research on the genetic conservation and evolution of areca nut resources, and areca nut genetic breeding.

The invention discloses a molecular identity card for identifying the variety of Tianhua mutton sheep and application of the molecular identity card, the molecular identity card is a specific SNP site combination for identifying the variety of Tianhua mutton sheep, the combination is composed of 36 SNP sites, is located in a sheep reference genome AR-UIRamv2.0, has high specificity and machine learning model classifier accuracy, and can be used for identifying the variety of Tianhua mutton sheep. The method can be used for identifying Tianhua mutton sheep, some varieties similar to the Tianhua mutton sheep in appearance and other genetic resource varieties of Gansu Province sheep. According to the invention, variety-specific molecular markers are screened at a genome level through a bioinformatics technology, genetic differences between Tianhua mutton sheep and some varieties with similar appearances and other genetic resource varieties of Gansu Province sheep can be revealed, and the Tianhua mutton sheep can be identified through a machine learning classifier and genetic evolutionary tree analysis according to characteristic SNP (Single Nucleotide Polymorphism). Guarantee is provided for fighting against counterfeit and shoddy varieties and reasonably protecting and utilizing variety resources of Tianhua mutton sheep.

The present invention belongs to the technical field of molecular biological identification, and discloses a molecular marker for identifying wild Wuzhishan oil-tea camellia, its application and detection method. The present invention provides a new InDel molecular marker for Wuzhishan oil-tea camellia resources. Using this molecular marker, it is possible to distinguish and identify Wuzhishan oil-tea camellia, which has been confirmed as a new species. According to the found InDel molecular markers, specific primer pairs for detecting these InDel sites are designed, and a detection method is created, which can accurately distinguish Wuzhishan oil-tea camellia from other oil-tea camellia species, and the detection results are accurate and reliable. The present invention has important application significance for scientifically protecting the diversity of Wuzhishan oil-tea camellia germplasm resources, studying the genetic protection and genetic evolution of Wuzhishan oil-tea camellia resources, and the genetic breeding of Wuzhishan oil-tea camellia.

The invention provides application of a pig SNP (Single Nucleotide Polymorphism) molecular marker combination in pig variety identification, a kit and an identification method, relates to the technical field of biology, and develops an SNP molecular marker combination for accurately identifying a plurality of pig varieties by applying a whole genome association analysis method for 18 wild boar varieties and 42 domestic pig varieties. By detecting the combination, a plurality of pig varieties can be accurately and efficiently identified, and the accuracy reaches 99.9%. The method is expected to provide a new variety identification technical means for pig variety right identification, germplasm resource protection and utilization, genetic evolution research and other demands.

The invention discloses a canine parvovirus CPV-2c subtype virus strain and application thereof, and relates to the technical field of biology. The canine parvovirus CPV-2c subtype virus strain is preserved in the China Center for Type Culture Collection on November 12, 2024, the preservation address is Wuhan University, Wuhan, China, and the preservation number is CCTCC NO: V202492. Genetic evolution analysis shows that the canine parvovirus CPV-2c subtype virus strain obtained through separation has a better genetic relationship with other epidemic strains published domestically. The strain has good pathogenicity, can show typical CPV clinical symptoms when infected dogs, has great advantages for verifying therapeutic drugs and evaluating vaccine efficacy in vivo, and plays an important role in research and development of the therapeutic drugs and vaccines. In addition, the strain can be cultured and proliferated in vitro and has the potential of being developed into vaccines.

The invention belongs to the technical field of breeding planning, and particularly relates to a large model construction method and system for multi-source data collaboration pear precision breeding planning, and the method comprises the steps: obtaining a multi-source collaboration data set, constructing a five-dimensional incidence matrix, and building a unified correlation basis of multi-dimensional data; constructing a constrained knowledge expression structure and training a constraint consistency reasoning model on the basis, analyzing a user breeding instruction in a constraint driving mode, and generating a combined constraint condition set containing a gene feasible region and a multi-phenotype collaborative target; calling germplasm resources under a cross-domain feature alignment and feature-level desensitization framework, executing phenotype-genotype collaborative screening, parent dynamic matching and multi-generation genetic evolution deduction, and generating breeding planning simulation data; and finally, outputting an optimal breeding scheme through a multi-dimensional evaluation system, and continuously updating the model by utilizing verification data. According to the invention, unification of multi-phenotype balanced synergistic improvement and stable gene transfer is realized, and the breeding efficiency and variety adaptability are remarkably improved.

The invention, which relates to the technical field of artificial intelligence, discloses an AI multi-currency change parking control system comprising a central calculation module, a currency identification module, a classified access module and an interactive display module. The central calculation module accumulates the parking time length based on the vehicle license plate and the confirmation signal, sends the total consumption amount, calculates the total payment amount and the total change amount through an accumulative change decision method, and generates a change scheme; the currency identification module obtains a payment currency grey-scale map and cooperatively identifies payment real currency and payment amount by adopting KL transformation and a genetic evolution back propagation network; the classified access module stores payment genuine coins in a classified manner, executes a change scheme, and decides whether to send a change stock supplement prompt or a full stock prompt based on a stock change principle; and the interactive display module senses user operation to generate a vehicle license plate or a confirmation signal, and displays the display information in real time, so that an automatic intelligent system integrating three functions of accurate recognition, optimal change and automatic supplementary prompt is realized.

The present invention provides a method for user grouping of a millimeter wave massive MIMO system based on a genetic algorithm, which adopts a survival of the fittest genetic mechanism to perform user grouping. From a genetic point of view, dynamically adjusting the user grouping method to ultimately achieve stable grouping is a genetic evolutionary process, in which different user groups constitute different elites in a generation, and the genes (or sub-individuals) of the elites are crossed to produce new offspring, and the parent generation and offspring are simultaneously subjected to preferential treatment to complete the natural selection mechanism, and finally a stable user grouping is obtained. Compared with the early heuristic method, the present invention has a greater advantage in performance; compared with the greedy method, its complexity is significantly reduced while the performance is similar.

An efficient technique of machine learning is provided for training a plurality of convolutional neural networks (CNNs) with increased speed and accuracy using a genetic evolutionary model. A plurality of artificial chromosomes may be stored representing weights of artificial neuron connections of the plurality of respective CNNs. A plurality of pairs of the chromosomes may be recombined to generate, for each pair, a new chromosome (with a different set of weights than in either chromosome of the pair) by selecting entire filters as inseparable groups of a plurality of weights from each of the pair of chromosomes (e.g., “filter-by-filter” recombination). A plurality of weights of each of the new or original plurality of chromosomes may be mutated by propagating recursive error corrections incrementally throughout the CNN. A small random sampling of weights may optionally be further mutated to zero, random values, or a sum of current and random values.

The application discloses a kind of dynamic depth analysis engine construction methods based on genetic evolution algorithm, belong to software analysis technical field, main in solving the problem of low code coverage and malicious behavior trigger rate of existing dynamic analysis technology, main scheme includes step 1: the UI level capture of being tested Android application is carried out to obtain UI component information in the tested Android application, obtain UI level information.Step 2: specified UI event trigger is realized by injecting event function.Step 3: capture software dynamic behavior characteristic data and realize malicious behavior dynamic detection using neural network model.Step 4: event function sequence is generated and screened using genetic evolution algorithm, and the injected event function is changed by feedback regulation.The application finally realizes the dynamic optimization of UI event sequence by combining with feedback regulation while detecting malicious behavior, and realizes the identification of Android malicious software based on dynamic analysis with high trigger rate.

The invention relates to a single-machine scheduling method based on reinforcement learning enhanced genetic evolution. The method comprises the following steps: setting problem parameters of single-machine total advance scheduling; constructing and optimizing a workpiece assignment probability model based on deep reinforcement learning, and inputting problem parameters of single machine total advance scheduling to obtain an initial solution set; and optimizing the initial solution set by using a genetic evolutionary algorithm to obtain an optimal single-machine scheduling scheme. Compared with a traditional method, the searching pressure of the optimization method can be relieved, the searching capability of the optimization method can be improved, and the solving efficiency and quality of the single-machine scheduling problem can be improved. Meanwhile, population hybrid initialization and population hybrid updating operation based on a workpiece assignment probability model are adopted, and through the hybrid population initialization operation, the population diversity can be guaranteed, and the initial population quality can be improved; and population mixed population updating operation is adopted, so that population evolution can be ensured, and gene diversity can be increased. Compared with a traditional method, it can be ensured that the algorithm considers both local search and global search capabilities.

The invention discloses a heat dissipation control method and device based on flip-chip bonding. The method comprises the following steps that S1, temperature information in the flip-chip bonding process is collected in real time; s2, pumping a nanofluid coolant through the micro through hole to take away heat generated in the chip bonding process; s3, inputting the collected temperature information into a temperature control regulation module, and adaptively optimizing the flow velocity of the coolant through fuzzy reasoning and a genetic evolution mechanism; s4, continuously receiving temperature feedback of each monitoring point, comparing a preset safety threshold value with the change trend curve in real time, and performing dynamic adaptive adjustment on a temperature control strategy; and S5, after bonding is completed, bottom filling and curing are carried out, and the chip packaging process is completed. According to the method, a high-thermal-conductivity material structure, nanofluid cooling and an intelligent optimization algorithm are fused, efficient heat management and dynamic self-adaptive temperature control in the flip chip packaging process are achieved, and the packaging reliability and the system intelligence level are effectively improved.

The invention relates to the technical field of grass carp geographic population identification, in particular to application of a single SNP and multi-SNP marker combination in identification of seven grass carp geographic populations. According to the application, the SNP locus genotype of the grass carp is associated with the geographic information of the grass carp, the geographic information of the grass carp is judged through the SNP locus genotype, and the geographic population of the grass carp is determined. The method provided by the invention can accurately and efficiently identify seven grass carp geographical populations. The method provided by the invention provides a new grass carp new germplasm identification technical means for the requirements of grass carp geographical population right identification, germplasm resource protection and utilization, genetic evolution research and the like.

The invention relates to a parameter optimization method and system based on ultra / extra-high voltage AC power transmission lines. The method comprises the following specific steps: obtaining wire parameters related to a spatial electric field intensity value in each ultra / extra-high voltage AC power transmission line; the genetic evolution optimization method based on bionic characteristics performs binary unified coding on wire parameters related to spatial electric field intensity values in all wires to form a population sequence required by the genetic evolution method, and performs unified serialization on all the wire parameters subjected to binary coding to obtain an initial population; based on the initial population, executing the following genetic evolution method: fitness selection: obtaining a space electric field intensity value of each ultra / extra-high voltage alternating current transmission line, calculating the fitness of each lead parameter in the initial population according to the space electric field intensity value, and then setting a selection probability according to the size of the fitness value of each lead parameter in the same proportion, and conducting wire parameter selection is carried out by using a roulette method.

The application discloses ginkgo polymorphic EST-SSR molecular marker primers and application thereof, and belongs to the technical field of molecular marker development and application thereof. EST-SSR sites are screened from ginkgo transcriptome data, and 100 pairs of primers are designed and synthesized. Through effectiveness verification and polymorphism screening with 141 ginkgo germplasm genomic DNAs as templates, finally, 20 pairs of specific EST-SSR molecular marker primers with good stability and high polymorphism are obtained. The application further discloses application of the self-developed molecular marker primers in ginkgo genetic diversity analysis and core germplasm construction and the like. The EST-SSR molecular marker primers provided by the application provide theoretical and technical support for ginkgo genetic evolution analysis, kinship identification and good seed selection and the like, and have important value for rational utilization, preservation and protection of ginkgo germplasm resources.

The invention discloses a social network rumor suppression method based on a genetic evolution model. The method comprises the following steps: firstly, constructing a symbol network, and constructing an SIR propagation model based on the symbol network; after a fitness function for evaluating the immune effect of the node set is established, the node set is continuously optimized by utilizing a genetic evolution algorithm framework, immune operation is performed on the nodes even if the nodes do not have propagation capability, and the scale of infected nodes in the network after propagation is stable is calculated as the fitness of the set; and repeating the operation until the number of iterations reaches a specified MaxGen, and outputting the optimal individual of the last round as the optimal solution of the algorithm result. According to the method, symbol characteristics in the symbol network are considered, compared with an existing immune method, the immune effect of the symbol network can be effectively improved, and key nodes on the symbol network can be recognized more accurately to suppress rumor propagation.

This application relates to a time-varying vehicle delivery route planning method and platform considering traffic flow. The method includes: using the NSGA-II algorithm to perform genetic evolution on multiple initial dual-encoders to generate multiple candidate dual-encoders; decoding and generating delivery planning information associated with each delivery object based on the node codes and delivery codes of all candidate dual-encoders; using the ant colony algorithm to perform time-varying vehicle delivery route planning based on the acquired time-varying travel time and delivery planning information to generate the intended delivery route corresponding to each delivery object; performing corresponding genetic evolution on all candidate dual-encoders based on the delivery fitness corresponding to the intended delivery route; and performing time-varying vehicle delivery route planning based on the delivery planning information and time-varying travel time of the dual-encoders that have completed the genetic evolution operation; and repeating the steps of performing the corresponding genetic evolution operation and performing time-varying vehicle delivery route planning until the target delivery route is generated.

The invention discloses an application of a donkey-derived biological component in analysis of human HBV or satellite virus infection thereof. The donkey sodium ion / taurocholic acid co-transport peptide close to a human source is obtained through genetic evolutionary tree analysis and screening, further experiments prove that the donkey sodium ion / taurocholic acid co-transport peptide can support human HBV and / or satellite virus infection thereof, and donkey primary hepatocytes can support human HBV and / or satellite virus infection thereof. The method can be used for constructing an economic and efficient HBV animal infection model, and has important significance on antiviral research or drug development of HBV and / or satellite viruses thereof.

The invention discloses a data cross-region migration method and device, electronic equipment and a storage medium. The technical problems that a current data cross-region migration strategy is single in consideration factor, low in migration efficiency and high in operation cost are solved. The method comprises the steps of obtaining to-be-migrated data and at least one target storage area of data cross-region migration; based on the to-be-migrated data, performing multi-factor analysis on each target storage area to obtain a multi-factor analysis result of each target storage area; on the basis of the multi-factor analysis result of each target storage area, optimal scheduling combining divide-and-conquer and parallel genetic evolution is carried out on the to-be-migrated data, and an optimal data migration scheme is obtained; and migrating the to-be-migrated data to at least one target storage area based on the optimal data migration scheme.

The invention discloses a source tracing data layering and grading method and device based on a genetic bionic model algorithm, data management and processing are optimized by referring to a genetic evolution principle in nature, and a data management mode combining a genetic algorithm and a data layering and grading management thought is combined. The method aims at optimizing the data classification and grading process by simulating genetic mechanisms such as selection, crossover and variation in the biological evolution process, so that the data management efficiency and safety are improved, the method can be applied to multiple aspects such as data classification, storage and retrieval in a big data environment, and the data processing efficiency and accuracy are improved. Moreover, traceable basic model data with obvious label attributes can be formed, and great convenience is brought to the regional power grid in combination with hierarchical and hierarchical data management.

The present invention relates to the field of biopharmaceutical technology, and particularly relates to a seasonal influenza A universal Mosaic recombinant antigen, its vaccine and application. The present invention analyzes the amino acid sequences of HA and NA of all human-derived H1N1 and H3N2 from 2009 to 2021 that are known, and uses the Mosaic design strategy to obtain influenza virus HA and NA Mosaic recombinant antigen sequences with the maximum diversity of potential T cell epitopes that can cover natural sequences; the influenza virus HA and NA Mosaic recombinant antigens designed by the present invention are assembled from short peptides of natural sequences. Through antigen epitope coverage analysis, genetic evolution analysis and spatial conformation analysis, they have a high antigen coverage rate, are closely related to vaccine strains and have good structural similarity with natural proteins, and have the potential to be developed into vaccine antigens.

The application discloses a D / Yama2019 genetic evolution lineage influenza D virus reverse genetic manipulation system. Seven pairs of primers are designed to amplify DNA fragments corresponding to full-length genome PB2, PB1, P3, HEF, NP, M and NS segments of D / JY3002, and the DNA fragments are cloned into pHW2000 and pCC1-DualPro vectors to construct a plasmid, and the plasmid is co-transfected into a cell line to obtain artificially rescued D / Yama2019 genetic evolution lineage influenza D virus rD / JY3002. The genome sequence of rD / JY3002 is completely consistent with that of natural isolated strain D / JY3002, and the infection ability is equivalent, and the rD / JY3002 can be stably passaged for at least five generations. A unidirectional expression plasmid pPolI-D / JY3002-PB1-240-GFP-240 is constructed to obtain artificially rescued recombinant influenza D virus rD / JY3002-GFP carrying a green fluorescent reporter gene, and after the rD / JY3002-GFP infects host cells, the GFP expression amount is high and stable. The application establishes a high-efficiency and stable D / Yama2019 genetic evolution lineage influenza D virus reverse genetic manipulation system, and can be used for developing an influenza D virus vector to present an exogenous gene.

The invention discloses an SNP molecular marker combination for identifying taro germplasm resources and application, and belongs to the technical field of molecular biology. According to the invention, 252 SNP loci are screened out and used for developing the PARMS-SNP marker, and 27 original PARMS-SNP markers are successfully obtained. 27 SNP markers are utilized to carry out genetic typing on 72 taro resources, and population structure analysis, PCA principal component analysis and genetic evolution analysis are further carried out. The taro germplasm resources can be well distinguished, and reference is provided for evaluation and identification of the taro germplasm resources and breeding of new germplasm.

The invention discloses a flow type blood sample pretreatment method and system based on a mechanical arm, and relates to the technical field of flow cytometry, the method comprises the following steps: obtaining operation information and layout information of a to-be-treated sample, and coding based on the operation information and the layout information to obtain sample features; generating an initial chromosome population based on the sample features; performing genetic variation treatment on the initial chromosome population to obtain a target optimized population, and selecting a target chromosome meeting a preset fitness condition from the target optimized population; and determining the trajectory planning scheme corresponding to the target chromosome as a target trajectory scheme, and controlling the mechanical arm to execute sample pretreatment operation on the to-be-treated sample according to the target trajectory scheme. According to the method, the sample information is obtained and feature coding is performed, so that trajectory optimization is performed by adopting the genetic evolutionary algorithm based on the sample features, the moving trajectory scheme of the mechanical arm can fully consider the features and layout of the samples, and the synchronism and the overall efficiency of sample processing are improved.

The application relates to a process mapping optimization method and device based on a genetic algorithm and a storage medium. The method comprises the following steps: obtaining communication data corresponding to a plurality of sub-processes of a target computing program, wherein the communication data comprises process communication volume and process communication time delay; performing real number coding on the process communication volume and the process communication time delay to generate a first process mapping coding array, wherein the first process mapping coding array comprises a plurality of first codes, and the first codes are used for representing the corresponding relationship between a first process core for executing a sub-process and the sub-process; performing genetic evolution operation on the first codes based on the genetic algorithm, performing redundancy scheduling processing on the first codes after the genetic evolution operation, and generating a second process mapping coding array with a plurality of second codes; determining the fitness of the second codes, and performing genetic evolution operation updating on the second codes in the second process mapping coding array according to the fitness to generate a target process mapping coding array, so that a process mapping optimization result is obtained.

The application discloses a SNP molecular marker combination for identifying taro germplasm resources and application, and belongs to the technical field of molecular biology. 252 SNP sites are screened for the development of PARMS-SNP markers, and 27 original PARMS-SNP markers are successfully obtained. 72 taro resources are subjected to genetic typing by using the 27 SNP markers, and population structure analysis, PCA principal component analysis and genetic evolution analysis are further carried out. The taro germplasm resources can be better distinguished, and reference is provided for the evaluation and identification of taro germplasm resources and the breeding of new germplasm.