38 results about "Genetic Databases" patented technology

A single cell sequencing data interpolation method based on a biclustering and graph convolutional neural network comprises the following steps: 1) respectively downloading matrix-form gene expression data of human and mouse from a gene database, and screening out cells of which the total number of gene expressions is less than 3 and genes of which the total number of cell expressions is less than 200; 2) performing feature selection on the gene expression matrix, finding out cells with consistent growth trend, forming a new two-dimensional matrix, and constructing a cell connection diagram; 3) constructing a BiGCN single-cell interpolation model by using a graph convolutional neural network, learning a nonlinear relationship between cells, dividing a data set into a training set and a test set, training the model by using the training set, and reserving the trained BiGCN single-cell interpolation model; 4) inputting the test set into the trained BiGCN single cell interpolation model to obtain an interpolation result, and evaluating the interpolation result by using an evaluation index; the method has the characteristics that the feature extraction capability is improved, interference of redundant zero expression is avoided, data sparsity is effectively relieved, and the interpolation accuracy is improved.

The invention relates to a digital intelligent regulation and control preparation method and system for a high-solid-waste low-carbon high-performance grouting material, and solves the problems that a traditional preparation technology lacks an autonomous and controllable digital intelligent regulation and control system and is weak in adaptability to fluctuation of raw materials, and the method comprises the following steps: obtaining XRF chemical components and XRD mineral composition data of industrial solid waste raw materials; constructing a material gene database; based on the database, screening a proportioning scheme by using a performance prediction model, and predicting workability, strength development and shrinkage performance; inputting a prediction result as a fitness function into a multi-objective optimization algorithm, and outputting an optimal material gene combination; a batching scheme is generated based on the optimal combination, and a stirring process is started after technological parameters are preset; collecting data through a real-time monitoring system, and comparing the data with the digital twin model; and based on a comparison result, automatically adjusting material proportioning parameters. The high-solid-waste, low-carbon and high-performance grouting material has the advantages that accurate design and regulation of the high-solid-waste, low-carbon and high-performance grouting material are achieved, material performance is improved, and carbon emission and cost are reduced.

The invention relates to the technical field of information, and provides a cross-platform global weed gene database unified building method which comprises the following steps: screening out a weed population having gene exchange characteristics with a target crop, identifying gene segments of gene exchange between the crop and weeds by adopting a gene comparison method, and determining a transmission path of resistance genes in interspecific hybridization; according to a gene comparison result, extracting transmission path data of the resistance gene, and analyzing the influence of resistance gene transmission on the genetic structure of the weed population in combination with the genetic structure characteristics of the weed population; calculating the frequency distribution of the resistance genes in different weed populations, judging the diffusion trend of the resistance genes in the weed populations according to the frequency distribution, generating a resistance gene diffusion map, and predicting the variation trend of the future weed population genetic structure based on a weed population genetic structure variation trend chart and the resistance gene diffusion map. And a global weed gene database is established, so that an effective weed management strategy can be formulated.

The invention relates to the technical field of knowledge graph construction, in particular to a method for constructing a knowledge graph of autism multi-source heterogeneous big data. Original data is obtained from an electronic medical record system, a gene database, a research literature library and a social media multi-source heterogeneous data source in a real-time or timing mode; 2, cleaning, denoising, missing value completion and de-identification are carried out on the original data, and standardized mapping is carried out on terms based on a unified medical language system, the fifth edition of 'Mental Diagnostic and Statistical Handbook' and a human phenotype ontology medical ontology; 3, on the basis of the medical ontology, autism related concept subsets are expanded, version control is carried out, and a special autism ontology is formed. According to the method, high-precision fusion of multi-source entities is achieved, and the technical bottlenecks that standardization mapping is difficult, extraction precision is low, fusion alignment is difficult and the like are fundamentally solved.

The application discloses a disease transmission link prediction method and system based on a dynamic hypergraph neural network, aiming to comprehensively depict virus transmission paths and risk levels from multiple dimensions. First, data is collected from a gene database, mobile device logs and clinical texts, virus variation characteristics, population contact relationships and symptom semantic information are extracted respectively, and a dynamic hypergraph that integrates virus strain nodes, individual nodes and regional nodes is constructed. The hyperedge is defined according to molecular similarity, space-time contact and semantic overlap, and the weight is dynamically adjusted according to the transmission intensity of the infectious disease. A multi-modal hypergraph neural network with variation perception is introduced to jointly model and adaptively fuse multiple types of hyperedges and multi-scale features, output node propagation embedding vectors and predict potential transmission chains, perform prevention and control responses, and realize real-time deployment and feedback loop in an edge-cloud collaborative manner, ensuring efficient and accurate infectious disease transmission modeling and intervention control while ensuring data privacy.

The invention discloses an RNA (Ribonucleic Acid) binding protein enrichment analysis method based on single cell expression profile data, which comprises the following steps of: writing an interactive online Web application program by using Shiny, carrying a data visualization tool, and using an RBP (Reactive Binding Protein)-gene database as a database; the method is specially designed for single cell data, different single cell data can be integrated for enrichment analysis, and expression profiles and RBP dynamic changes in single cells can be effectively captured and analyzed; rBP enrichment analysis is customized for single cell data, a single group and multiple groups of single cell expression data are preprocessed, including normalization processing, and a statistical model is used to evaluate enrichment significance at each time point, so that the analysis accuracy and biological correlation are improved; a dynamic visualization tool is provided, the dynamic visualization tool comprises a customizable network diagram, an interactive bar diagram and detailed table display, and a user can adjust a plurality of parameters of a view according to needs and directly download images and data from an interface.

The invention discloses a disease transmission link prediction method and system based on a dynamic hypergraph neural network, and aims to comprehensively describe a virus transmission path and a risk level from multiple dimensions. The method comprises the following steps: firstly, collecting data from a gene database, a mobile equipment log and a clinical text, respectively extracting virus variation characteristics, a crowd contact relationship and symptom semantic information, and constructing a dynamic hypergraph fusing virus strain nodes, individual nodes and region nodes; the hyperedge is defined according to molecular similarity, space-time contact and semantic overlap, and the weight is dynamically adjusted along with the infectious disease transmission intensity. A multi-modal hypergraph neural network of variation perception is introduced, joint modeling and adaptive fusion are performed on multi-type hyperedge and multi-scale features, a node propagation embedded vector is output, a potential propagation chain is predicted, prevention and control response is executed, and real-time deployment and feedback closed loop are realized in an edge-cloud cooperation mode. And efficient and accurate infectious disease transmission modeling and intervention control are completed on the premise of ensuring data privacy.

The invention provides an HLA typing method and an electronic device thereof. The method comprises the following steps: S1) comparing sequencing data of each sample gene with an HLA gene database to obtain a first candidate HLA gene typing set; s2, in the first candidate HLA genetic typing set, typing results with the coverage degree smaller than 30% or the average sequencing depth smaller than 30 * are filtered, and a second candidate HLA genetic typing set is obtained; s3) according to the consistency sequence of the corresponding sample gene in each typing result in the second candidate HLA gene typing set, the typing results which are different from the coding region of the corresponding consistency sequence in the coding region of the sample gene are filtered, a final HLA typing result is obtained, and the sample HLA gene is obtained through sequencing of a three-generation sequencing platform.

The application belongs to the technical field of gene detection, and discloses a method and system for judging the influence of homologous regions in NGS gene variation detection. The method comprises the following steps: obtaining a first type of gene and a plurality of second type of genes according to a public database; obtaining corresponding original sequence files of the first type of gene and the second type of gene based on a local gene database, obtaining corresponding sequence alignment files based on a local BAM database, and combining them to obtain known NGS gene data; calculating the GC content, the proportion of repeat units, and the similarity ratio in the original sequence file, and calculating the alignment quality in the corresponding sequence alignment file to construct a training sample; inputting the training sample into a classification model to obtain an optimized classification model; extracting the GC content, the proportion of repeat units, the similarity ratio, and the alignment quality from the NGS gene data to be detected and inputting them into the optimized classification model to judge whether the variation detection is affected. The application can judge the influence of homologous regions in variation detection without the aid of prior information of homologous regions.

The present application provides a method, device, computer equipment and medium for detecting pathogenic genes. Among them, the method includes: screening the genes in the extracted cells based on the pathogenic gene database, and determining the pathogenic gene set; determining the pathogenic gene carrying value according to the pathogenic gene set; comparing and analyzing the pathogenic gene carrying value according to the historical gene detection data, and outputting the detection result. Among them, the pathogenic gene database includes a variety of pathogenic genes. The pathogenic gene set is a set of genes in the extracted cells that are the same as the pathogenic genes in the pathogenic gene database. The pathogenic gene carrying value is used to indicate the proportion of key pathogenic genes in the genes of the extracted cells. Through the above method, the pathogenic genes that the target object may carry can be detected more comprehensively, and the risk of disease of the target object can be predicted so as to prepare in advance.

The invention discloses a biodiversity investigation monitoring method based on satellite remote sensing and environmental DNA sequencing. The method comprises the following steps: S1, acquiring habitat remote sensing data and environmental DNA data; s2, preprocessing the obtained data, and comparing the preprocessed data with a public gene database to obtain species distribution data; s3, performing time and space scale alignment and fusion on the habitat remote sensing data and the environment DNA data to generate a biodiversity feature data set; and S4, constructing and generating a correlation model and a three-dimensional model between the habitat and the species distribution, and visually displaying the dynamic change of the biodiversity. According to the method, the comprehensiveness, accuracy and timeliness of investigation and monitoring are improved, and a scientific basis is provided for biodiversity protection.

The application discloses a biodiversity investigation and monitoring method based on satellite remote sensing and environmental DNA sequencing, comprising the following steps: S1, obtaining habitat remote sensing data and environmental DNA data; S2, preprocessing the obtained data and comparing with a public gene database to obtain species distribution data; S3, aligning and fusing the habitat remote sensing data and the environmental DNA data in time and space scales to generate a biodiversity feature data set; and S4, constructing a correlation model and a three-dimensional model between the habitat and the species distribution, and visually displaying the dynamic change of biodiversity. The application improves the comprehensiveness, accuracy and timeliness of investigation and monitoring, and provides a scientific basis for biodiversity protection.

The invention provides a Mena antisense oligonucleotide and a preparation method of the Mena antisense oligonucleotide. The antisense oligonucleotide is antisense oligonucleotide targeting a Mena gene core sequence, five antisense nucleic acids are analyzed in a wisdom gene database, and it is found that no sequence identical to the antisense nucleic acid target sequence exists, so that the four antisense nucleic acids do not generate an off-target effect. The ASO-Mena can be used for effectively inhibiting the scratch healing speed of lung cancer cells. The ASO-Mena1, 2 can inhibit lung cancer cell metastasis, and almost has no toxic influence on normal cells.

The invention discloses a single cell annotation method and system based on gene sensitivity. The core process of the method comprises the following steps: firstly, extracting a related Marker gene list from a gene database to construct a reference data set; establishing an undirected network based on a protein interaction relationship of an effective Marker gene in a to-be-annotated cell, quantifying a gene comprehensive network weight by means of a network centrality index, performing probabilistic conversion on gene expression data, calculating gene divergence in combination with expression distribution, and determining a scarcity index according to the occurrence frequency of a reference data set. And then integrating the three to obtain a gene sensitivity index, introducing machine learning to fuse gene importance weight to eliminate divergence when annotation divergence of a cell and a clustering level exceeds a threshold value, and finally determining an annotation classification result according to comprehensive matching score of the cell to a known type.

The application discloses a kind of based on graph reinforcement learning's document-level event causal relationship identification method, comprising the following steps: obtaining text data containing event;Using large language model as external knowledge base and reasoner, generating prior causal graph, obtaining initial graph structure;Using long text pre-training language model to obtain the representation of contextualization event and calculate the correlation degree of event pair, provide prior knowledge;Introduce attention mask and self-attention initialization mechanism, generate the representation of contextualization event, integrate prior causal graph and contextualization event correlation into Transformer model to guide and control the training of model;Using graph reconstruction loss and attention distribution offset regularization loss to train and optimize model;Output the causal relationship between events extracted in gene database. The application introduces the self-attention initialization mechanism based on event correlation, and limits the attention of Transformer in reasonable distribution space.

The presently described techniques relate generally to configuration and use of a software platform (156) that provides tools for users to store, arrange, and visualize genetic data, such as may be derived from a nucleic acid sequencing device (144). Such a software platform (156) may include one or more tools that allow a user to annotate genetic data with information available from external and / or internal genetic databases and to create custom reports based on such information.

The invention relates to the technical field of cable insulation thickness measurement, in particular to a cable insulation thickness measurement method and system based on an alternating curvature driving algorithm, and the method comprises the steps: collecting a cable cross section image, extracting an inner edge contour and an outer edge contour from the cable cross section image, obtaining an inner edge pixel coordinate set and an outer edge pixel coordinate set, respectively importing the inner edge pixel coordinate set and the outer edge pixel coordinate set into two pre-constructed blank arrays to obtain an inner edge pixel coordinate array and an outer edge pixel coordinate array, constructing an inner edge curvature gene database and an outer edge curvature gene database, generating an inner edge initial population and an outer edge initial population, and constructing an inner edge curvature gene database and an outer edge curvature gene database; and obtaining an optimal inner adaptation degree set and an optimal outer adaptation degree set, obtaining an optimal insulation thickness measurement coordinate set, and completing cable insulation thickness measurement based on the alternating curvature driving algorithm based on the optimal insulation thickness measurement coordinate set. According to the invention, the average detection time can be shortened and the minimum insulation thickness deviation can be improved.

The application provides a method for HLA typing and an electronic device thereof. The method comprises the following steps: S1) comparing the sequencing data of each sample gene with an HLA gene database to obtain a first candidate HLA gene typing set; S2) filtering the typing results with a coverage less than 30% or an average sequencing depth less than 30x in the first candidate HLA gene typing set to obtain a second candidate HLA gene typing set; S3) filtering the typing results with differences in the coding regions of the sample genes from the corresponding consensus sequences in the second candidate HLA gene typing set to obtain a final HLA typing result, wherein the sample HLA gene is obtained by sequencing with a third-generation sequencing platform.

The invention belongs to the field of gene identification, and particularly relates to a method for identifying an invasive plant in a soil environment DNA sample by using chloroplast genome data, which comprises the following steps: constructing an invasive plant chloroplast whole-genome database; collecting samples at a plurality of sample points; eDNA in the sample is extracted; carrying out PCR (Polymerase Chain Reaction) amplification on the extracted eDNA to obtain an amplicon product; sequencing the amplicon product by using a high-throughput sequencing technology to obtain high-throughput data; comparing the intrusive plant chloroplast whole-genome database with the high-throughput data to obtain the species of the intrusive plant species; according to the method, only the extracted eDNA is subjected to chloroplast gene PCR amplification, and exfoliates of animals and microorganisms are screened out, so that the DNA data volume is simplified, and the analysis of invasive plant species in a region can be accurately and comprehensively completed.

The invention discloses a digitization method for breeding black-bone chickens, which belongs to the field of poultry breeding, and comprises the following steps: digitization in a breeding stage: screening breeding hens by using big data analysis and gene detection technologies, avoiding close breeding, and improving the quality and hereditary stability of baby chicks. By establishing a breeding hen gene database and analyzing genetic information of breeding hens, breeding hens with excellent characters are selected for hybridization, and healthy and high-quality chicks are bred. Automatic regulation and control of the breeding environment, accurate feeding and real-time monitoring of the growth condition are achieved through the digital technology, manual intervention is reduced, and the breeding efficiency is improved. The intelligent feeding system can accurately feed the black-bone chickens according to the actual requirements of the black-bone chickens, feed waste is avoided, and the breeding cost is reduced. Meanwhile, breeding environment parameters are automatically regulated and controlled, optimal growth conditions are provided for the black-bone chickens, growth and development of the black-bone chickens are promoted, and the breeding cycle is shortened.

The present invention discloses an automatic screening method, system, device and storage medium for gene editing sites, the method comprising: obtaining the gene name and species name, and obtaining the sequence, transcript information and position information of the gene on the chromosome from a gene database; determining the candidate knocking region according to the position information and transcript information; performing GC content and complexity analysis on the candidate knocking region to determine the knocking region; sorting the knocking region according to the number of common transcripts and position information; according to the sorting, intercepting the knocking region sequence from the sequence of the gene through the position information of the knocking region; obtaining all gRNAs and corresponding specificity scores and cutting efficiency scores of the knocking region sequence from the gRNA online design software, and determining and displaying the editing site of the gRNA according to the specificity score and cutting efficiency score. The embodiment of the present invention can automatically and efficiently screen gene editing sites with good knockout effect, strong specificity and high cutting efficiency, and can be widely used in the field of gene editing technology.

This application provides a method, system, medium, product, and terminal for constructing a gene relationship knowledge graph. The method involves acquiring gene data from different databases and preprocessing the gene data; extracting entity information from the preprocessed gene data using a natural language model to generate an initial gene entity dataset and an initial gene entity relationship graph; performing data filtering on the initial gene entity dataset based on an adaptive filtering algorithm to obtain a target gene entity dataset; and constructing a gene relationship knowledge graph based on the target gene entity dataset, the initial gene entity relationship graph, and a pre-built gene database model. This not only comprehensively reveals the entirety of the gene network and its dynamic changes but also intuitively displays the interactions between genes through visualization, providing researchers with an intuitive and convenient research tool.

The present application relates to a screening system and method for plant directional breeding, comprising: a collection unit configured to acquire images of a plant to be tested, and a central controller comprising a gene database storing gene data associated with phenotype changes of the plant to be tested, the central controller being configured to generate phenotype data of the plant to be tested related to a development time node according to the images acquired by the collection unit, and divide the phenotype data into at least one data set based on a development stage of the plant to be tested, the central controller setting a keyword label of an associated phenotype change for the data set corresponding to the development stage, and generating a recommended gene set corresponding to the keyword label through the gene database, wherein the recommended gene set is a set of genes associated with changes in the development time node of the plant to be tested.

The present invention discloses a genome-based equipment framework application design method, system and device, including: S1, building a genome database; S2, performing gene-performance mapping analysis and gene-environment effect mapping analysis based on the gene database to obtain analysis results and store them in the gene database; S3, performing engineering practice application based on the analysis results. The present invention is based on the equipment genome concept of equipment planning demonstration, engineering development and test identification framework.

The invention discloses a method for detecting gelatin in sea cucumber based on a fluorescent PCR (Polymerase Chain Reaction) technology. The method comprises the following steps: determining a target and designing a primer and a probe; determining a target gene: selecting a mitochondrial gene aiming at the DNA which is easy to degrade after processing, and designing a primer and a probe for amplifying a short fragment; obtaining a specific sequence: obtaining target gene sequences of the target sea cucumber and common adulterated species from an NCBI gene database, and finding a unique specific sequence region of the sea cucumber through comparison; synthesizing a primer and a probe: designing and synthesizing the primer and the TaqMan probe on the basis of the specific region; preparing a reference substance; sample pretreatment and DNA extraction; preparing a fluorescent PCR reaction system and adding a sample; running a fluorescent PCR amplification program: placing the reaction tube in a real-time fluorescent quantitative PCR instrument; result analysis and interpretation: quality control inspection and sample result interpretation. According to the invention, a primer and a probe which are only complementarily combined with sea cucumber DNA are designed, and a fluorescence signal is generated in PCR amplification, so that specific detection can be realized.

The application relates to a digital intelligent control preparation method and system of high-solid-waste low-carbon high-performance grouting material, solves the problem that a traditional preparation technology lacks a self-controllable digital intelligent control system and has weak adaptation capability to material fluctuation, and the method comprises the following steps: obtaining XRF chemical component and XRD mineral composition data of industrial solid waste materials, and constructing a material gene database; based on the database, a performance prediction model is used to screen a proportioning scheme, working performance, strength development and shrinkage performance are predicted; the prediction result is input into a multi-objective optimization algorithm as a fitness function, and an optimal material gene combination is output; based on the optimal combination, a batching scheme is generated, a stirring process is started after presetting process parameters; data are collected through a real-time monitoring system and compared with a digital twin model; based on the comparison result, material proportioning parameters are automatically adjusted. The application has the following effects: precise design and control of high-solid-waste low-carbon high-performance grouting material are realized, material performance is improved, and carbon emission and cost are reduced.

The invention discloses a method for constructing an RNA interference vector of pathogenic genes of rice bakanae disease pathogenic bacteria, and relates to the technical field of genetic engineering.The construction method comprises the steps that pathogenic gene segments are obtained, specifically, the pathogenic gene sequences of the rice bakanae disease pathogenic bacteria are retrieved from a gene database, specific primers with specific restriction enzyme recognition sites are designed, and the specific primers are used for identifying the pathogenic genes of the rice bakanae disease pathogenic bacteria; the method comprises the following steps: carrying out PCR (Polymerase Chain Reaction) amplification by taking pathogenic bacteria genome DNA as a template, and recovering and purifying a target gene segment after agarose gel electrophoresis separation; by optimizing the construction process of the RNA interference vector, efficient silencing of a target gene is achieved, specific restriction enzyme recognition sites and specific primers are utilized, pathogenic gene segments of pathogenic bacteria of the rice bakanae disease are retrieved and amplified from a gene database, and the pathogenic gene segments of the pathogenic bacteria of the rice bakanae disease are obtained. And then the RNA is connected and transformed with an intermediate vector and a plant expression vector to finally obtain the RNA interference vector capable of silencing the pathogenic gene, and the method has higher construction efficiency and more accurate silencing effect.

The present invention relates to the field of information technology, and provides a method for uniformly constructing a global weed gene database across platforms, including: screening out weed populations with gene exchange characteristics with target crops, using gene alignment methods to identify gene fragments of gene exchange between crops and weeds, and determining the transmission path of resistance genes in interspecific hybridization; according to the gene alignment results, extracting the transmission path data of resistance genes, and combining with the genetic structure characteristics of the weed population, analyzing the impact of the transmission of resistance genes on the genetic structure of the weed population; calculating the frequency distribution of resistance genes in different weed populations, judging the diffusion trend of resistance genes in the weed population according to the frequency distribution, generating a resistance gene diffusion map, and based on the weed population genetic structure change trend map and the resistance gene diffusion map, predicting the future change trend of the weed population genetic structure, uniformly constructing a global weed gene database, which helps to formulate effective weed management strategies.

Biomarkers for post-traumatic stress disorder (PTSD) and biomarkers for fibromyalgia (FM), which is associated with a high rate of PTSD, have been identified by narrowing down biomarker genes from PTSD-related gene database on the basis of biological events related to disease conditions. In addition, Chinese herbal medicines that are potential therapeutic agents for PTSD have been identified through the examination and comparison of gene induction by Chinese herbal medicines and antipsychotics in human keratinocytes. The present method can provide: biomarkers applicable as indicators for the diagnosis and the development of therapeutic agents for PTSD and FM; effective Chinese herbal medicines for PTSD and FM; and a screening method for therapeutic agents for PTSD and FM.

The invention relates to the technical field of biomedical treatment, and discloses a chronic inflammatory disease risk prediction method and system and a storage medium. The method comprises the following steps: acquiring and cleaning original sequence data related to chronic inflammatory diseases from a patient gene database, and constructing a structured variation interaction network; real-time physiological indexes and health status data are fused, and an enhanced variation feature set reflecting gene-environment interaction is extracted through feature propagation technologies such as a graph convolutional network; analyzing in combination with a historical health data time sequence record, and generating a time sequence enhanced variation feature sequence; generating a preliminary risk score sequence by dynamically evaluating the weight of the risk factor in the sequence; through probability distribution modeling, deviation correction and multi-source verification, a comprehensive risk prediction value for the chronic inflammatory disease is obtained; and generating a risk assessment report based on the predicted value. According to the invention, dynamic, accurate and personalized prediction of the chronic inflammatory disease risk is realized.