161 results about "Sequence analysis" patented technology

The invention discloses a steam turbine safe operation health assessment method and system, and belongs to the technical field of steam turbine monitoring. The method comprises the following steps: acquiring running data of a steam turbine in real time through a multi-source sensor network deployed on key components of the steam turbine; the method comprises the following steps: preprocessing original operation data of a steam turbine by adopting edge computing equipment to generate a time domain waveform analysis diagram or a time sequence analysis diagram; transmitting the preprocessed structured feature data to an operation and maintenance management platform, inputting a fault diagnosis model for analysis, pre-training through a historical fault case library, and aligning feature distribution of the historical case library and current equipment data through a domain adaptive algorithm in transfer learning; and inputting a diagnosis result into a self-adaptive dynamic evaluation model based on a reinforcement learning engine, dynamically adjusting a model weight and an alarm threshold according to real-time working condition parameters, outputting a health score and a maintenance decision, and forming a closed-loop process of perception-edge processing-cloud diagnosis-dynamic optimization-decision output.

The invention discloses a diopter detection data fusion processing system based on deep learning, and relates to the technical field of medical detection. The system comprises a multi-modal data acquisition module, a data preprocessing and aligning module, a dynamic sequence analysis module, a deep learning regression core module, a personalized calibration module and a result output and visualization module which are connected in sequence. The system obtains objective detection data through a multi-modal data acquisition module, and multi-modal data is formed after preprocessing and space-time alignment; the dynamic sequence analysis module extracts adjustment response time sequence features; the deep learning regression core module calculates an initial diopter parameter; the personalized calibration module performs parameter optimization in combination with the biological characteristics of the user; and finally, a visual quality simulation result is generated through a result output and visualization module. According to the method, the multi-modal data fusion and deep learning technology is utilized, rapid and accurate diopter automatic detection is realized, and the detection efficiency and the individuation level are remarkably improved.

The invention discloses an anomaly detection method and system for transaction flow data, and relates to the technical field of big data analysis. The method comprises the following steps: based on transaction flow data, acquiring operation behavior data of a target user in a transaction process and interaction behavior data after the transaction is completed, and sorting according to timestamps to form a user operation behavior sequence and a user interaction behavior sequence; inputting the sequence into a pre-trained abnormal risk prediction model, and outputting an initial risk coefficient, wherein the model integrates an individual behavior baseline and an adaptive weight module; acquiring a group behavior baseline of the similar user group, and correcting the initial risk coefficient in combination with a matching result of the sequence and the group baseline to obtain a final risk coefficient; and performing classification abnormity early warning operation on the final risk coefficient based on a preset risk threshold. According to the method, through whole-process behavior sequence analysis, individual and group baseline dual calibration and dynamic weight adjustment, the accuracy and timeliness of transaction flow data anomaly detection are effectively improved.

The invention relates to the technical field of artificial intelligence application, and discloses an enzyme EC number prediction method, and the method comprises the steps: obtaining the sample sequence characteristics of a to-be-predicted sample containing a substrate SMILES sequence and a product SMILES sequence through a target BERT model; constructing a molecular object and feature coding based on atom mapping, atom truncation and sequence analysis, constructing a reaction graph of a to-be-predicted sample, inputting the reaction graph into a target graph isomorphic neural network, and constructing molecular graph features of the to-be-predicted sample based on a recursive neighborhood aggregation mechanism; and fusing the sample sequence features of the to-be-predicted sample with the molecular map features by using a bidirectional cross attention mechanism to obtain multi-modal features, inputting the multi-modal features into the multi-layer perceptron, and obtaining the prediction probability of the enzyme EC number of the to-be-predicted sample. According to the method, efficient and accurate end-to-end prediction of enzyme EC numbering is realized through the multi-dimensional chemical spatial characteristics of the collaborative modeling reaction.

The invention relates to a nucleic acid aptamer for specifically recognizing tilmicosin as well as screening and application of the nucleic acid aptamer, and belongs to the technical field of food safety detection and biosensing. Aiming at the defects of the existing method for detecting tilmicosin residues in food, the invention provides a high-affinity and high-specificity nucleic acid aptamer obtained by screening based on a graphene oxide index enrichment ligand systematic evolution technology. The aptamer is obtained by multiple rounds of screening from a random single-stranded DNA library through a GO-SELEX technology, and a core sequence Apt-2-1 with the length of 33 nt is finally obtained through sequence analysis and structure optimization. The aptamer shows excellent binding capacity to tilmicosin, the dissociation constant reaches 9.82 nM, and the aptamer has good specificity. The nucleic acid aptamer provided by the invention can be used for constructing a rapid and sensitive tilmicosin residue detection method, and has important application value in monitoring of livestock and poultry products and food safety.

The invention provides a toxoplasma gondii gene deletion strain with an immune protection effect and application of the toxoplasma gondii gene deletion strain, and belongs to the technical field of veterinary parasitology, veterinary immunology and parasite molecular biology. According to the toxoplasma gondii gene deletion strain, a gamma-glutamyl hydrolase gene is deleted. The invention also provides a method for constructing the insect strain. The method comprises the following steps: constructing a circular plasmid pSAG1-Cas9-U6-sgGGH; constructing a repair template containing upstream and downstream homologous arms of the gamma-glutamyl hydrolase gene and a DHFR resistance gene; co-transfecting the annular plasmid and the repair template to a toxoplasma gondii ME49 strain; performing drug screening on pyrimethamine to obtain positive monoclone; and confirming that the GGH gene is completely knocked out through PCR (Polymerase Chain Reaction) detection, sequencing analysis and immunofluorescence detection. The toxoplasma gondii gene deletion strain can provide a remarkable protection effect on toxoplasma gondii infection and is high in safety.

The application discloses an mRNA vaccine sequence design system and method based on a large language model intelligent agent, and the mRNA vaccine sequence design system based on the large language model intelligent agent comprises a user interaction and task analysis module, a task planning and intelligent agent scheduling module, an RNA design skill library and skill description module, a multi-target evaluation and closed-loop optimization module and a data and model management module. The application integrates a large language model and various mRNA sequence analysis and optimization tools, automatically completes mRNA vaccine sequence generation, evaluation and optimization for a target antigen in a computer environment, is suitable for candidate sequence design and screening of a preventive or therapeutic mRNA vaccine, improves design efficiency, and reduces the degree of dependence on manual experience and manual script arrangement.

The invention provides an optical cable fault intelligent analysis and positioning method based on big data and AI, and the method comprises the steps: extracting a spatial density feature value from a latitude and longitude coordinate set, judging the coordinate as a high-density region coordinate if the spatial density feature value exceeds a preset threshold value, and obtaining a preliminary spatial distribution point set; performing grouping processing on the preliminary spatial distribution point set by adopting a clustering algorithm, fusing Euclidean distance measurement in the longitude and latitude coordinate set, determining a cluster of fault points, and obtaining a distribution mode cluster group; and performing prediction processing on a time sequence of the high-incidence area identification set through a time sequence analysis algorithm, fusing trend data of the time evolution sequence segment, determining a prediction value of a future evolution rule, and obtaining a prediction rule value set.

The invention relates to an intron variant capable of accurately splicing and enhancing gene transcription and application of the intron variant, and belongs to the technical field of biological breeding, the intron variant is a variant of a Cat1mu intron, the Cat1mu intron has a nucleotide sequence as shown in SEQ ID NO.2, and the nucleotide sequence of the intron variant is formed by mutating base AG at the 182th to 183th sites of the sequence as shown in SEQ ID NO.2 into tG, Ac, At, cG, Aa, ta, tt, tc, cc, ct or ca. According to the present invention, the sequence analysis and the saturation mutation are performed on the Cat1mu, the screening is performed to obtain the Cat1mu series variant Cat1mu2-12, the accurate splicing effect of the Cat1mu2-12 during the fusion gene expression process is verified, and the Cat1mu6, the Cat1mu7, the Cat1mu8 and the Cat1mu10 can further enhance the fusion gene expression effect.

This invention relates to the field of bioinformatics, and particularly to a method and system for denoising single-cell immune repertoire sequencing data. The method includes data preprocessing and feature extraction, bidirectional collaborative denoising, intelligent comprehensive judgment and classification, data archiving and background learning, and result output. Compared to existing technologies that primarily rely on static thresholds for cell filtering, which struggle to comprehensively assess and eliminate multi-dimensional noise, leading to incomplete purification and the potential deletion of high-value cell information, this invention employs a systematic denoising scheme integrating multi-parameter dynamic threshold filtering, specific gene contamination analysis, and targeted optimization of VDJ data. It sets dynamic thresholds by integrating multi-dimensional quality control indicators such as UMI number, gene number, and the proportion of mitochondrial and ribosomal genes, and specifically identifies and filters interfering genes and background sequences. This enables refined and hierarchical removal of complex noise, significantly improving the overall quality of cell datasets and the accuracy of VDJ receptor sequence analysis.

The invention discloses a real-time estimation method for tail water flow of aquaculture. The method comprises the following steps: firstly, comprehensively collecting basic environment data of geographic position, landform, water quality and geometric dimension of an aquaculture pond, and arranging and storing the data; secondly, monitoring the initial flow velocity, flow direction and cross sectional area change of the water flow at the tail water discharge port in real time by using professional equipment, and transmitting data according to preset intervals; then analyzing interference factors such as wind power, tide and cultivated organism activity, constructing a correlation model to correct water flow state parameters, and preliminarily estimating instantaneous flow based on a water flow dynamics algorithm; and predicting a flow change trend through time sequence analysis, and constructing an incidence matrix optimization estimation value in combination with production activity data. And finally, the accurate estimated value is transmitted to a culture management system database in a JSON format through a Modbus protocol, and key data support is provided for scientific management. According to the method, a more scientific, efficient and accurate solution is provided for estimating the tail water flow in the aquaculture industry.

The invention provides application of bacillus altitudinis H18 and a glucoside hydrolase gene thereof in improving rumen degradation of rice straws, and belongs to the technical field of straw reutilization. The bacillus altitudinis H18 is separated from goat rumen fluid, the bacillus altitudinis H18 can promote degradation of rice straw cellulose, and reference is provided for feed application of rice straw. Sequencing analysis finds that a whole genome of the strain H18 contains a large number of genes related to glucoside hydrolase GH, carbohydrate hydrolase CE and the like, and the content of neutral detergent fibers and lignin in the rice straw can be remarkably reduced by performing fermentation treatment on the rice straw by using the strain H18 through an in-vitro fermentation method. The strain can be used as a bacterial strain for feed application of the rice straws so as to improve the conversion rate and the utilization rate of the rice straws.

The invention provides a reinforcement learning sequential sequence analysis system and method based on deep hybrid experts, and the system comprises a preprocessing module which carries out the denoising of a sequential sequence, and carries out the division of the denoised sequential sequence according to a fixed window size, and obtains a preprocessed sequential sequence; the strategy network is used for coding and decoding the time sequence processed by the preprocessing module on the basis of a hybrid expert layer to obtain scoring information of the time sequence; and the weight generator is used for obtaining the weight of each time sequence based on the scoring information of the strategy network. Through the data preprocessing module, the strategy network and the weight generator, better sequential sequence feature extraction and better sequential sequence scoring are realized.

The invention provides a space transcriptome data analysis system based on a PDX model, and relates to the technical field of biological information analysis. Comprising the following steps: extracting a coordinate identifier, a molecular identifier and a sample transcript sequence in a sequencing sequence; analyzing a sample transcript sequence, and preliminarily classifying a sequencing sequence into a first sequence, a second sequence, an uncertain sequence and a discarded sequence; calculating a first ratio under each sub-box; classifying the sub-boxes into a first sub-box and a second sub-box according to the first ratio; re-classifying the uncertain sequences in the first sub-box into a first sequence, and re-classifying the uncertain sequences in the second sub-box into a second sequence; and S104, respectively merging and analyzing all the first sequences and the second sequences to obtain a first space gene expression profile and a second space gene expression profile. According to the method provided by the invention, the distribution accuracy of the gene expression quantity of the space transcriptome and the utilization rate of the sequencing sequence are improved.

The present disclosure provides a MNP marker primer combination for macadamia variety identification, a kit and its application. The primer combination comprises: 1st-446th primer pairs, forward primer of 1st primer pair, reverse primer of 1st primer pair to forward primer of 446th primer pair and reverse primer of 446th primer pair, which are sequentially shown in SEQ ID NO: 1-SEQ ID NO: 892 in the sequence listing. Using the MNP marker primer combination, DNA fingerprint data of the sample to be tested can be obtained by multiplex PCR amplification and high-throughput sequencing, and then compared with the control sample to obtain the genetic similarity coefficient, and finally obtain the variety identification conclusion of the sample to be tested and the control sample, and the accuracy and digitization degree are both high. A sequence analysis software can be used to compare hundreds of samples to be tested at one time, and the variety identification conclusion can be quickly obtained, which can significantly improve the accuracy and efficiency of macadamia variety identification.

The application relates to the field of biomedical technology, in particular to a heavy chain and light chain variable region gene sequence of a LSDV ORF123 monoclonal antibody, an expression immunoglobulin full gene sequence and application thereof, the application extracts total RNA of hybridoma cells (1G1-1G12) by hybridoma sequencing, takes mRNA in the total RNA as a template, carries out reverse transcription to obtain cDNA of corresponding antibody genes, and then uses specific PCR to obtain a heavy chain variable region (Variable region of heavy chain, V H ) and a light chain variable region (Variable region of light chain, V L ) of the corresponding antibody, and carries out cloning and sequencing analysis. Finally, the heavy chain and light chain variable region gene nucleotide sequences of a monoclonal antibody (1G1-1G12) targeting the LSDV ORF123 protein are obtained, and the application is realized. Sequence analysis of the heavy chain (V H ) and light chain antibody (V L ) of the above-mentioned monoclonal antibody shows that the V H and V L gene subtypes of 1G1-1G12 are as follows: the heavy chain is IgG type, and the light chain is kappa type.

The application discloses a target code segment acquisition method and device, relates to the technical field of computers, and can reduce the time cost and false positive rate of running sequence analysis. In the application, intermediate code of an application program and dynamic data including a running track function acquired when the application program is running are acquired, functions different from the running track function in the intermediate code are removed, and a target function of the intermediate code is obtained; running sequence analysis is performed on the target function, and a first target code segment in which the running sequence of the code in the target function is different from a preset sequence is obtained. Based on the target code segment acquisition method provided in the application, the analysis range of application program running sequence analysis can be reduced, and the time cost and false positive rate can be reduced.

An object of the present invention is to provide a design method, a manufacturing method, a design device, a design program, and a recording medium of a primer for amplicon methylation sequence analysis, which can improve a design success rate of the primer while suppressing the formation rate of a primer dimer extremely low.The present invention is a primer design method for amplicon methylation sequence analysis, including a primer sequence determination step of selecting one or more primer candidate sequence pairs related to a predetermined target site from one or more primer candidate sequences, calculating a local alignment score between predetermined primer sequences, and adopting and determining a primer candidate sequence pair having a score equal to or less than a predetermined threshold value as a forward primer sequence and a reverse primer sequence for amplifying a region including the predetermined target site.

The invention relates to the technical field of biology, in particular to a Zymomonas mobilis terminator library as well as a construction method and application thereof. Through terminator prediction, primer design, sequencing analysis and efficiency calculation, the stable and efficient Zymomonas mobilis terminator library with high robustness is obtained through screening. The terminator sequence in the library is low in repeatability and high in matching degree with a known transcription termination site. The library constructed by the invention can effectively avoid plasmid recombination, can be directly used for optimizing expression of key enzymes in a metabolic pathway, improves metabolic flux by enhancing mRNA stability, and provides an efficient tool for metabolic engineering modification of Zymomonas mobilis.

The application provides a molecular marker related to tail fat deposition of sheep, a detection method and application thereof. Through PCR amplification and sequence analysis of rBAT (SLC3A1) gene of the sheep, a C / T polymorphic site at the 689th position of the amplified fragment is found, further, the polymorphic site of 1286 Hu sheep is detected by using KASPar primers, a least square model is established, and correlation analysis of the genotypes and growth traits is carried out, and finally it is determined that the amplified RBAT gene fragment can be used as a molecular marker related to tail fat of the sheep. The application can be used for selecting and reserving TT homozygous sheep into a core group, for reducing tail fat deposition of the sheep, and for increasing economic benefits.

The invention provides a method for enriching bacteria and fungi in atmospheric environment biological aerosol. Research finds that when the filter membrane is used for enriching bacteria and fungi in the atmospheric environment biological aerosol, the surface of the filter membrane is coated with a protective agent, the enrichment number of the bacteria and fungi in the biological aerosol can be increased, the activity of the bacteria and fungi in the biological aerosol after enrichment can be maintained, and the protective agent comprises glycerin and / or trehalose. According to the method, the enrichment efficiency of bacteria and fungi in the biological aerosol can be remarkably improved, and the method has a wide application prospect in the aspect of subsequent sequencing analysis of microorganisms in the biological aerosol.

The invention discloses an illegal behavior prediction method, device and equipment and a computer readable storage medium. The method comprises the following steps: dynamically adjusting the weights of visible light and infrared characteristics through environmental parameters, ensuring that the most effective mode can be selected under different environmental conditions, and improving the robustness of prediction; feature extraction and alignment are carried out on visible light and infrared images, the problem of inconsistency of multi-source data is solved, and the representativeness and comparability of features are enhanced; based on weighted fusion features and an action position recognition model, the position and action category of the object to be recognized are accurately recognized, and in combination with time sequence behavior sequence analysis, the accuracy and timeliness of illegal behavior prediction are improved; and an alarm is triggered when the illegal behavior is predicted, so that active intervention is realized, and accidents on the construction site are effectively prevented.

The application provides a molecular marker related to immune traits of Lake sheep, a detection method and application thereof. Through PCR amplification and sequence analysis of a PD-L1 gene of the Lake sheep, a G / A polymorphic site at the 135th position of the amplified fragment is found, further detection of the polymorphic site of 898 Lake sheep is carried out by using KASPar primers, a least square model is established, and correlation analysis of the genotype and growth traits is carried out, and finally it is determined that the amplified PD-L1 gene fragment can be used as a molecular marker of immune traits related to the total number of red blood cells and the average concentration of hemoglobin of red blood cells of the Lake sheep. Through detection of the molecular marker, the application can be used for disease-resistant breeding of the Lake sheep, so as to guarantee the health of the Lake sheep and help to increase economic benefits.

The invention belongs to the technical field of Hu sheep molecular marker-assisted breeding, and particularly relates to application of an FABP3 gene molecular marker g.2596A > C in Hu sheep molecular marker-assisted breeding. According to the invention, Hu sheep is taken as a research object, PCR amplification, direct sequencing of products and sequence analysis are adopted, FABP3 gene polymorphism is analyzed, and correlation between different genotypes of polymorphic sites and different growth traits is comprehensively analyzed. An analysis result shows that g.2596A > C is obviously related to the birth weight of Hu sheep, and the birth weight of AA genotype is obviously higher than that of CC genotype (P > 0.05).

The invention discloses an mRNA vaccine sequence design system and method based on large language model intelligent proxy. The mRNA vaccine sequence design system based on the large language model intelligent agent comprises a user interaction and task analysis module, a task planning and intelligent agent scheduling module, an RNA design skill library and skill description module, a multi-target evaluation and closed-loop optimization module and a data and model management module. According to the method, the large language model and various mRNA sequence analysis and optimization tools are integrated, mRNA vaccine sequence generation, evaluation and optimization aiming at the target antigen are automatically completed in a computer environment, the method is suitable for candidate sequence design and screening of prophylactic or therapeutic mRNA vaccines, the design efficiency is improved, and the design cost is reduced. And the degree of relying on artificial experience and manual script arrangement is reduced.

The invention discloses a degrading bacterium system for repairing pesticide-polluted soil and application of the degrading bacterium system. The degrading bacterial system is composed of Pseudomonas plecoglossa JY-5, Klebsiella plecoglossa J2-1, Arthrobacter silvisoli JY-2 and Enterobacter ludwigii JY-1, and the degrading bacterial system is obtained by carrying out enrichment culture, screening, sequencing analysis and bacterial strain identification and purification on the soil polluted by the pesticide, and the degrading bacterial system is used for degrading the soil polluted by the pesticide, and the degrading bacterial system is used for degrading the soil polluted by the pesticide and the soil polluted by the pesticide and the soil polluted by the pesticide and the soil polluted by the pesticide and the soil polluted by the pesticide and the soil polluted by the pesticide and the soil polluted by the pesticide. According to the degrading bacterium system, the biochar is used as a carrier to prepare an immobilized bacterium agent, various common pesticides such as carbendazim and the like can be efficiently degraded, the strains have a synergistic effect, the stability in a complex soil environment is high, the anti-interference capability is outstanding, soil pesticide residues can be effectively reduced, an efficient and feasible technical scheme is provided for soil remediation in a pesticide high-pollution area, and the degrading bacterium system has wide application prospects. The method has important practical application value.

The invention relates to the technical field of artificial intelligence, big data mining and complex time sequence analysis, in particular to an AI quantization time sequence feature adaptive extraction algorithm system, which comprises a space-time multi-dimensional adaptive purification module used for optimizing a data signal-to-noise ratio through a volatility ratio and a time period mask; the microstructure sensing feature construction module is used for constructing a relative feature space and extracting fractal and entropy features; the dynamic asymmetric volatility label generation module is used for generating a balanced sample label based on the average real wave amplitude; the double-path parallel integration representation learning module is used for performing prediction through Bagging and Boosting path fusion; and the closed-loop feedback optimization module is used for feeding back and optimizing system parameters according to the simulation objective function. The method comprises corresponding steps. According to the method, the problems that the features lack state perception, sample construction destroys physical significance and the like are solved, and high-robustness and self-adaptive evolution time sequence feature extraction and trend identification are realized.

A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes a integrated circuit formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the integrated circuit connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.

The application provides a molecular marker related to feed conversion rate of sheep and application thereof in breeding. The application finds that a T / C polymorphism site exists at the 233th position of an amplified fragment by performing PCR amplification and sequence analysis on an APOD gene of sheep, further detects the polymorphism site of 897 Hu sheep by using AQP primer pairs, establishes a least square model, performs correlation analysis on the genotypes and the feed conversion rate, and finally determines that the amplified APOD gene fragment can be used as the molecular marker related to the feed conversion rate of sheep. The molecular marker can be used for breeding of a new breed of high-quality meat sheep with grain-saving, and provides a genetic engineering means for genetic improvement of the feed conversion rate of sheep, and has great practical application value.

The invention relates to an mRNA (messenger Ribonucleic Acid) codon sequence language modeling method based on a bidirectional Mama framework, which comprises the following steps of: acquiring an mRNA coding sequence, performing sequence tokenization on the mRNA coding sequence, and querying by adopting a word list to obtain an embedding characteristic; the embedded features are sequentially input into a convolution feature extraction module and a state space module of a bidirectional Mamba model to generate collaborative representation, and meanwhile, each time step serves as an affine pair and is used for carrying out inter-block synthesis on block-level pairs to obtain a synthesis result; and inputting the collaborative representation and synthesis result into a bidirectional branch and linear fusion module to obtain a linear transformation fusion result, projecting the linear transformation fusion result to a word list dimension, obtaining a cross entropy and a model parameter used for training a bidirectional Mama model, and generating a target dimension vector of each sequence by using the trained bidirectional Mama model. According to the invention, the accuracy and expandability of mRNA sequence analysis and design can be improved.