88 results about "Sequence comparison" patented technology

The invention belongs to the field of molecular biological identification, and particularly relates to a specific SNP (Single Nucleotide Polymorphism) site combination for identifying a Wuzhishan pig variety and application. The specific SNP site combination for identifying the Wuzhishan pig variety comprises 77 SNP sites, and the physical positions of the SNP sites are determined by sequence comparison based on a pig reference genome Sscrofa11.1. The specific SNP site combination is screened based on a method of combining whole genome association analysis with selection signal analysis so as to ensure the accuracy of site selection. The selected specific SNP site combination can rapidly realize accurate identification of the Wuzhishan pig variety on the gene level, and has significant application value in the aspects of genetic resource accurate protection and variety utilization of Hainan Wuzhishan pigs.

The invention provides a protein language model pre-training and protein mutation method and related products. According to one specific embodiment of the protein language model pre-training method, a sample protein data set is obtained; generating a multi-sequence alignment probability distribution sequence corresponding to the sample protein data according to the amino acid residue probability distribution of multiple sequences in each sample protein data alignment at each site; the sample protein sequence in each sample protein data and the corresponding multi-sequence comparison probability distribution sequence and structure sequence are sequentially connected in series in the forward direction or the reverse direction, and a multi-modal sequence corresponding to the corresponding sample protein data is generated; and finally, performing autoregression pre-training on the protein language model based on the multi-modal sequence corresponding to each sample protein data to obtain a pre-trained protein language model. Namely, the prediction performance of the model is improved by introducing a multi-sequence comparison probability distribution sequence as an independent intermediate reasoning mode and thinking chains in two directions.

The invention relates to the technical field of information retrieval, in particular to an academic supply and demand dynamic sensing method and system based on space-time big data, and the method comprises the following steps: obtaining the path length of a source and a target college, screening migration direction stable labels, recognizing a trend consistent region, evaluating the local transfer capacity, and fusing a high-frequency path region. And extracting behavior track data, performing sequence comparison on the associated nodes, and generating a prediction chain space offset mark set. According to the method, space label units with stable migration characteristics are effectively distinguished by processing enrollment information and population migration trends and constructing a path length filtering and direction section repeating mechanism, and supply and demand migration origin areas are accurately locked in combination with change trends reflected by continuous direction consistency; spatial aggregation judgment is enhanced through a statistical means of a neighborhood capacity proportion and path intersection frequency, the sensitivity and dynamic response capability of a spatial prediction structure are improved, and active sensing and intervention prompting of a supply and demand change trend under multiple space-time dimensions are realized.

The invention provides a disease marker epitope prediction and antibody screening method, which belongs to the technical field of disease markers, and comprises the following steps: firstly, establishing a training data set containing a known antigen-antibody compound structure and disease tissue expression data; and obtaining target protein sequence information through liquid chromatography-mass spectrometry analysis and carrying out sequence comparison. And then a deep convolutional neural network is utilized to extract sequence features, and surface exposure sites are identified by combining secondary structure prediction and solvent accessibility analysis. After the features are integrated with sequence evolution conservative properties, a prediction model is constructed by using a random forest classifier. The method comprises the following steps: carrying out molecular dynamics simulation on a prediction result, screening first 10% of candidate sequences through a comprehensive scoring function and K-means clustering, and finally determining an antigen epitope sequence with the strongest binding activity through verification of an antigen chip and a fluorescence labeled antibody system, so that the technical problem that specific antigen epitopes are difficult to accurately predict and recognize in the prior art is solved.

The invention discloses a somatic mutation recognition method and system based on a residual network in combination with a channel attention mechanism, and the method comprises the steps: scanning a sequence comparison result of a tumor sample and a paired normal sample, and constructing a multi-channel feature matrix representation; a somatic mutation recognition model combining a residual network (ResNeXt) and a channel attention mechanism (SE module) is constructed, verification and fine tuning are performed by using a test set, and then the somatic mutation recognition model which is excellent in performance and suitable for resource-constrained environment deployment is obtained. The invention provides a new hybrid neural network, the network fully utilizes sequence comparison result information of a tumor sample and a paired normal sample, somatic mutation information can be extracted and learned more effectively, and mutation recognition accuracy is improved.

A protein multi-conformation prediction method based on flexible residue probability distribution comprises the following steps: firstly, expanding a self-constructed protein data set by utilizing an ATLAS molecular dynamics simulation database so as to enhance the capturing capability of a model on protein dynamic information; secondly, extracting multi-sequence comparison features and structural features of the protein, and inputting the features into a deep learning network based on a residual network module for training; on this basis, a protein flexible residue probability graph is further generated, dynamic behaviors and conformation change information of the protein are fully mined, then the flexible residue probability graph is used for guiding multi-sequence alignment MSA mask operation, MSA of masks in different areas at different depths is constructed and input into an AlphaFold2 model, and finally the protein multi-conformation structure is generated. According to the method, the efficiency and precision of protein multi-conformation prediction are remarkably improved, and a more efficient and accurate solution is provided for protein multi-conformation prediction.

The invention belongs to the technical field of molecular biology, and particularly discloses a primer capable of identifying five acer species at the same time and application of the primer, the primer comprises AcerTS-F: CGGAACTAGTCGGATGGAGT; the invention relates to a method for preparing an Ac < S-R >: GAAGCAGTTCGAGACAACCG; respectively extracting total DNA (deoxyribonucleic acid) of acer palmatum, acer mono, acer ginnala, acer tegmentosum and acer mogmentosum plants; carrying out PCR (Polymerase Chain Reaction) amplification on the total DNA (Deoxyribose Nucleic Acid) of each species by using the AcerTS-F and the AcerTS-R; after PCR products are sequenced, sequence comparison is carried out, five acer species including acer northeast, acer mono, acer ginnala, acer tegmentosum and acer mogmentosum can be identified at the same time, and precious genetic resources are provided for genetic diversity, phylogenetic evolution and taxonomy research of the acer species.

The invention provides a method for predicting the interaction relevance between ncRNA (non-coding ribonucleic acid) and protein based on MLP-Mixer. The method comprises the following steps: firstly, coding a protein / ncRNA sequence by combining a k-mer method; inputting the sequence features into a hybrid network combined with an MLP-Mixer network so as to extract the sequence features; and finally, simulating interaction between nucleotide and amino acid through a double-sequence comparison attention module, and outputting the interaction to a classification part for classification. According to the method, the first-level sequence features, the second-level structure sequence features and the third-level structure features are comprehensively considered, a multi-layer perceptron mixer module is introduced and is combined with the convolutional neural network and the bidirectional long-short-term memory network, and therefore the long-distance dependency between the features recognized by the CNN can be captured. Meanwhile, complex interaction between nucleotide and amino acid is simulated through a double-sequence comparison attention module, so that fine correlation between ncRNA and a protein sequence is explored.

The invention discloses a method for microfluidic high-throughput screening of AKK bacteria. The method comprises the following steps: 1) preparing a microfluidic chip; 2) collecting fresh excrement of healthy volunteers, diluting, and adding a fluorescence labeled antibody to obtain a dispersion phase; and (3) preparing liquid drops by taking paraffin oil and Span-80 as a mobile phase, enabling the liquid drops to enter a liquid drop culture tank through an S-shaped liquid drop circulation channel, culturing, introducing the mobile phase, introducing the liquid drops in the liquid drop culture tank into a liquid drop collection tank, taking out, detecting a fluorescence signal, culturing the liquid drops with the fluorescence signal on the improved brain heart infusion broth solid culture medium, and obtaining the brain heart infusion broth. Obtaining a to-be-identified strain; 4, the strain to be identified serves as a template, PCR amplification is conducted, sequencing is conducted on an amplification product, BLAST sequence comparison is conducted on a sequencing result on an NCBI website, and the target strain AKK bacterium is screened out. The method has the advantages of being high in throughput, simple in experimental process and high in specificity, and the screening efficiency of the AKK bacterium can be improved.

The invention belongs to the field of biological medicine, and relates to a detection reagent based on a nasopharyngeal carcinoma related TCR sequence and application of the detection reagent. The invention provides a storage assembly for storing data, the storage assembly stores instructions for diagnosing an individual suspected to suffer from nasopharynx cancer, receives input individual data, and the individual data comprises obtained sequences of TCR libraries in biological samples of the individual and obtained TCR library sequence information of the individual; analyzing TCR library sequence information of the individual and reference CDR3 beta amino acid sequence comparison information to obtain a TCR clone number completely matched with the reference CDR3 beta amino acid sequence, and obtaining a TCR score according to the obtained TCR clone number completely matched with the reference CDR3 beta amino acid sequence; and on the basis of the TCR score, outputting diagnosis information about whether the individual suffers from nasopharynx cancer or not. The storage assembly for storing data can be used to obtain a diagnostic system for diagnosing an individual suspected of having nasopharynx cancer. The diagnosis system disclosed by the invention can be applied to screening of high-risk groups with nasopharyngeal carcinoma, early diagnosis and treatment of nasopharyngeal carcinoma, evaluation of clinical prognosis and development of a new immunotherapy strategy.

The invention provides an SNP (Single Nucleotide Polymorphism) site combination, a molecular probe combination, a zucchini whole genome gene chip and application thereof, the SNP site combination comprises at least one SNP site in a table 1, and physical position information of the SNP site in the table 1 is determined based on a zucchini reference genome 22S20 or genome sequence comparison of an updated version of the zucchini reference genome 22S20. Specifically, the invention provides a zucchini whole genome 10K liquid-phase gene chip and application thereof. By adopting the zucchini whole genome 10K liquid-phase gene chip disclosed by the invention, high-depth re-sequencing can be carried out on target sites of zucchini, and accurate detection of genotypes of SNP (Single Nucleotide Polymorphism) sites is realized. Meanwhile, the zucchini whole genome 10K liquid-phase gene chip has the advantages of low cost and high efficiency, is beneficial to accelerating the breeding process of zucchini, and provides powerful technical support for development and utilization of zucchini germplasm resources.

The application relates to a detection method of anti-preS1 antibody, an anti-preS1 antibody detection kit and application, the application carries out multi-sequence comparison and conservation analysis on preS1 sequences of different genotypes (A, B, C, D and CD mixed type) of HBV, takes type A (AB697487.1), type C (FJ032351.1) and type D (LC519808.1) as reference sequences, based on the sequence consistency standard of 85% of full length and 90% of the key region of functional antibody binding, a highly conservative preS1 full-length antigen sequence is systematically screened out in natural variation, the sequence can cover antigen variation of A-D type HBV, and the sequence is taken as a coating antigen to establish an indirect ELISA detection system, a good linear relationship is presented in the range of 4.88-625 ng / mL, and the Cut-off value is 33.6 ng / mL; clinical verification shows that the method can effectively distinguish chronic hepatitis B patients from healthy control groups, compared with detection methods based on partial fragments or overlapping short fragments, the false negative rate can be significantly reduced, and the method is suitable for HBV infection immune state evaluation, anti-virus curative effect monitoring and prognosis analysis.

The invention provides an SNP (Single Nucleotide Polymorphism) site and method for identifying the trehalose content of a tetraploid potato tuber and application, the physical position of the SNP site is determined on the basis of sequence comparison of a chromosome 12 of a tetraploid potato'Qing potato No.9 'reference genome, and the SNP site comprises: an A2 haplotype SNP single nucleotide polymorphism site snp: 35849480, the polymorphism being A / G; the SNP single nucleotide polymorphism site snp of the A3 haplotype is 55777825, and the polymorphism is T / G; the SNP single nucleotide polymorphism site snp of the A4 haplotype is 46535012, and the polymorphism is A / G; the SNP single nucleotide polymorphic site snp of the A4 haplotype is 46568448, and the polymorphism is A / T. The invention provides an important molecular tool for efficient identification and genetic improvement of the trehalose content of the tetraploid potatoes.

The invention belongs to the technical field of biological detection, and relates to a bacterium 16s rDNA full-length RAA detection kit and a method for identifying bacteria by using the same. The kit comprises a primer pair for RAA amplification of bacterium 16srDNA full length, the sequence of an upstream primer of the primer pair is as shown in SEQ ID NO: 1, and the sequence of a downstream primer of the primer pair is as shown in SEQ ID NO: 2. According to the bacteria 16s rDNA full-length RAA detection kit and the method for identifying the bacteria by using the same, high-specificity, high-sensitivity and high-stability RAA amplification can be performed on the 16s rDNA full lengths of various bacteria in a sample to be detected, and amplification products are easier to quickly and accurately determine the species of the bacteria in the sample to be detected through sequencing and sequence comparison.

The invention belongs to the technical field of disease control in aquaculture, and particularly relates to a hippocampus enteritis pathogen separation and identification and medication screening method based on a high-throughput sequencing technology, which comprises the following steps: collecting intestinal tissues of a diseased hippocampus and a healthy hippocampus, respectively preparing tissue homogenate, and freezing for preservation; the method comprises the following steps: extracting DNA (Deoxyribose Nucleic Acid) of microorganisms of an intestinal tissue sample, performing 16SrDNA high-throughput sequencing, analyzing intestinal flora composition, and determining dominant bacteria; selecting and screening a culture medium according to dominant bacteria, and performing pathogenic bacterium separation and purification on intestinal tissues of the diseased hippocampus; dNA of the purified strain is extracted, 16S rDNA amplification and sequencing are carried out, and the species of pathogenic bacteria are identified through sequence comparison; according to the method, the diversity and abundance differences of microorganisms in the sick hippocampus and the healthy hippocampus are compared through a high-throughput sequencing technology, and targeted separation, identification and drug sensitivity screening are further carried out by taking statistically significant difference bacteria as the guidance of potential pathogenic bacteria.

The invention discloses a target pathogen detection method based on a feature vector hash table, software and application. Based on the combination of a deep learning neural network model and a K-mer sequence comparison technology, a K-mer sequence is converted into a feature vector considering local features and global features so as to predict possible species classification information. In the actual operation process, only the belonging-level reference hash table corresponding to the model prediction result needs to be loaded, and the whole genome reference database does not need to be loaded. Compared with the traditional method, the method provided by the invention has the advantages that the memory is reduced by 90% when the 136GB data is processed, the analysis time is shortened from more than 3 minutes to less than 10 seconds, and huge potential and practical application value are shown in large-scale sequencing application.

The invention belongs to the field of fish species and sex identification in the field of aquaculture, and discloses a specific DNA fragment combination for distinguishing female acipenser ussuriensis and female Huso dauricus and application. According to the invention, a segment of specific DNA fragment for distinguishing genders of female acipenser ussuriensis and female Huso dauricus is successfully screened through conventional PCR amplification, sequencing and sequence comparative analysis, primers are designed to accurately and rapidly identify genders of female acipenser ussuriensis and female Huso dauricus, and genders and female parent sources of female acipenser ussuriensis and female Huso dauricus individuals and hybrid generations thereof are distinguished. The invention also discloses a primer sequence, a PCR reaction system and conditions. The identification method disclosed by the invention is simple, rapid and accurate to operate, has extremely small harm to fish bodies, solves the problems of identifying the genders of the Russian sturgeon and the Huso dauricus, the female parent of the hybrid sturgeon and the caviar source, and is beneficial to the development of the sturgeon caviar industry.

The application discloses a molecular marker of citrus full mite resistance to ethyl acetazolamide and application thereof, and the molecular marker is SNP mutation A269G and / or T270A of succinate dehydrogenase SDHD subunit of the citrus full mite. A detection method of the molecular marker of the citrus full mite resistance to ethyl acetazolamide is also disclosed, total DNA of the citrus full mite to be detected is extracted, PCR amplification is carried out with the total DNA as a template, a succinate dehydrogenase SDHD subunit gene fragment containing a mutation region is obtained, and the obtained gene fragment is subjected to sequence comparison with the molecular marker, so that the resistance of the citrus full mite to be detected to ethyl acetazolamide can be judged. The molecular marker and the detection method can simultaneously detect a large number of samples, can quickly and effectively detect whether the resistance SNP molecular marker and the mutation proportion exist in a field population of the citrus full mite, and can evaluate the mutation frequency of the corresponding site in a certain geographical population.

The invention discloses a performance evaluation method and device for a hardware Trojan detection algorithm, equipment and a medium, and relates to the technical field of information security, and the method comprises the steps: controlling a hardware Trojan simulation circuit to generate a first pseudo-random sequence according to a random number seed issued by an upper computer; comparing the first pseudo-random sequence with a second pseudo-random sequence issued by an upper computer to obtain a sequence comparison result; if it is judged that the hardware Trojan simulation circuit meets the preset activation condition according to the sequence comparison result, an encryption protection removal circuit in the hardware Trojan simulation circuit is enabled to replace a side channel protection design circuit in the encryption circuit to operate; performing hardware Trojan detection on the to-be-detected circuit by using the hardware Trojan detection algorithm to obtain a detection result, and performing performance evaluation on the hardware Trojan detection algorithm based on the detection result; wherein the circuit to be detected is a coupling circuit of the encryption circuit and the hardware Trojan simulation circuit. And the performance of the hardware Trojan horse detection algorithm can be evaluated more reliably.

The invention discloses a one-stop tumor RNA-seq analysis system which comprises an original data quality control module, a sequence comparison and quantification module, a fusion gene analysis module, a variable shear analysis module, a differential expression analysis module, a function enrichment analysis module, an immune pathway module, a data management and visualization module and a containerization safety deployment module. The system receives an FASTQ format of original RNA-seq data, carries out quality evaluation and filtering, generates high-quality clean reads, generates gene expression quantitative data through sequence alignment, carries out differential expression, function enrichment and other analysis on the gene expression quantitative data, and carries out data management, visualization and safe deployment on an analysis result. The analysis system is high in data analysis efficiency and credible in analysis result, so that scientific researchers and biomedical workers can perform tumor RNA-seq data analysis more conveniently.

The application provides a two-dimensional data sequence comparison method based on similarity matching, comprising similarity matching of each row and each column of a target two-dimensional data sequence obtained; through a one-dimensional data sequence similarity matching method and a data set similarity matching method, index coordinates of data elements are repositioned by means of data characteristics and data structures; and according to pairing results between rows and between columns obtained, comparison of data elements between target two-dimensional data sequences is carried out in a targeted manner. The method fully considers the influence of data element positions on data comparison, and overcomes defects of the prior art in minimum difference identification between two-dimensional data sequences under conditions of index coordinate variation such as adjustment, increase and deletion of row or column positions.

The invention discloses a multi-constraint-based anti-parallel DNA triplex design method and system, and relates to the technical field of DNA triplex targeting genes, and the method comprises the following steps: constructing an mCGR initialization model, adjusting a matrix iteration rule according to a sequence length and a basic constraint, and generating all possible sequence sets satisfying the constraint; mapping the sequence set into flow network nodes, screening out approximate nodes through similarity search, constructing to-be-screened edges, then performing sequence comparison on the to-be-screened edges, only reserving the edges of the sequence within a preset stem length range, and deleting the edges beyond the range, so as to overcome the problem of high complexity of mCGR during combined constraint calculation; and finally, outputting a DNA triplex coding sequence meeting all constraint conditions. According to the method, the anti-parallel DNA triplex TFO sequence meeting multiple constraints can be efficiently generated, the sequence set scale is large, the stability is high, the crosstalk rate is low, and a key technical support is provided for research and development of nucleic acid drugs in the field of targeted gene therapy.

The invention discloses a foundation pit support dismantling monitoring method and system based on targeted analysis, and belongs to the technical field of data analysis. A foundation pit supporting system targeted three-dimensional model is constructed through a BIM model, key supporting components and high-risk targeted monitoring points are focused, and multi-direction stress sensors are arranged; an initialized simulation monitoring sample set and a real-time monitoring sample set are generated, and theoretical-actual dismantling sequence comparison is achieved; initial and real-time stress data clusters are called and planned as a whole, and construction specification expected conformity is evaluated through dual-targeting requirement conformity (sample set matching degree and stress data difference); if not, accurate early warning is triggered according to the stress deviation weight. The problems that traditional monitoring is poor in targeting, feedback lags behind and early warning is extensive are solved, the safety and controllability of the foundation pit dismantling process are improved, and the method is suitable for dismantling engineering of deep foundation pits and complex supporting systems.

The invention belongs to the technical field of oil and gas seismic exploration, and particularly discloses a sequence stratigraphic framework establishment method, device and equipment based on a high-precision age stratigraphic body and a medium. In the method, firstly, well-seismic comprehensive calibration is carried out by combining a well-connected sequence comparison result and a seismic data optimization processing result; then, on the basis of well-seismic comprehensive calibration, a sequence top and bottom grillwork model is constructed based on seed point tracking intelligent explanation; then, based on the sequence top and bottom framework model, age stratigraphic body tracking is carried out by adopting a plane wave decomposition method, and high-precision multi-layer interpretation is realized; and finally, constructing a high-precision sequence framework model by combining a well-connected sequence comparison result and high-precision multi-layer interpretation. According to the method, the sequence stratigraphic framework model which is finer, more accurate and higher in timeliness can be established, an important guiding effect is achieved for target conception and reservoir fine representation, and the method is suitable for sequence stratigraphic framework research in petroleum and natural gas seismic exploration.

The invention discloses a multi-sequence parallel comparison method based on maximum precision matching, and relates to the technical field of crossing of bioinformatics and computational biology. The method comprises the following steps: splicing character strings of a plurality of sequences to obtain a long sequence, and determining a suffix array and a longest common prefix array of the long sequence by adopting a mode of combining a bucket dividing strategy and induced sequencing; according to the suffix array, searching a maximum accurate matching fragment from the longest common prefix array, and screening an ordered and non-overlapped maximum accurate matching fragment set through a dynamic programming technology; expanding each maximum accurate matching fragment in the maximum accurate matching fragment set to all sequences to form a chain; segmenting the long sequence through a chain to obtain a plurality of sub-sequence sets; and calling third-party multi-sequence comparison software to compare the plurality of sub-sequence sets, and splicing the comparison result of each sub-sequence set to obtain a multi-sequence comparison result. According to the method, the time complexity of ultra-long or large-scale sequence data comparison is reduced.

The invention belongs to the field of molecular biological identification, and particularly relates to a specific SNP (Single Nucleotide Polymorphism) site combination for identifying a pier-head pig variety and application. The specific SNP site combination for identifying the pier head pig variety comprises 40 SNP sites, and the physical positions of the SNP sites are determined by sequence comparison based on a pig reference genome Sscrofa11.1. The specific SNP site combination is screened based on a method of combining whole genome association analysis with selection signal analysis so as to ensure the accuracy of site selection. The specific SNP site combination provided by the invention can quickly realize accurate identification of the variety of the pier-head pig at the gene level, and has remarkable application value in the aspects of accurate protection of genetic resources and variety utilization of local pigs in Hainan.

The invention discloses an identification method for variable splicing of a smelly spodoptera frugiperda antenna odor receptor gene and application of the identification method. According to the invention, the variable spliceosome protein of the key OR gene of the antenna is obtained by constructing a standardized identification method comprising'full-length transcriptome sequencing, bioinformatics screening, PCR amplification verification and sequencing verification, and sequence comparison ', and electrophysiologically active compounds are efficiently screened by taking the variable spliceosome protein as a target spot; the problems that in an existing prevention and control technology, a target spot cannot be accurately positioned, and the active compound screening efficiency is low are solved, and a molecular basis and technical support are provided for targeted interference of smelly recognition behaviors of spodoptera frugiperda and research and development of a novel pest prevention and control technology.

The application belongs to the field of molecular biology identification, and particularly relates to a specific SNP site combination for identifying Duntou pig breeds and application. The specific SNP site combination for identifying Duntou pig breeds comprises 40 SNP sites, and the physical position is based on the reference genome of pigs Sscrofa11.1 The sequence comparison is determined. The specific SNP site combination is screened based on the method of whole genome association analysis combined with selection signal analysis, so as to ensure the accuracy of site selection. The specific SNP site combination provided by the application can rapidly realize the accurate identification of Duntou pig breeds at the gene level, and has significant application value in the accurate protection of Hainan local pig genetic resources and breed utilization.

The invention discloses a primer group and a kit for detecting gene polymorphism of Alzheimer's disease, a method for detecting gene polymorphism and application, the primer group comprises forward and reverse PCR amplification primers aiming at each gene, a target gene segment is amplified through specific PCR, then an amplification product is sequenced by adopting a Sanger sequencing method, and the primer group and the kit are used for detecting the gene polymorphism of Alzheimer's disease. And comparing and analyzing a sequencing result through a software sequence to obtain the base polymorphism information of the target gene.

The present disclosure relates to the field of biological gene sequencing technology, including methods, devices, and media for generating a nanopore sequencing signal decoding model training set. A pre-trained basic model is used to perform base recognition on a sequenced current signal to obtain a decoding sequence and decoding path corresponding to the current signal; the decoding sequence is compared with a reference sequence corresponding to the current signal; based on the sequence comparison results, at least two first subsequences in the decoding sequence whose recognition accuracy meets a first preset condition are determined; based on the sequence positions corresponding to different first subsequences in the reference sequence, second subsequences between different sequence positions are extracted in the reference sequence; based on the decoding path, the current signal corresponding to the second subsequence is determined in the current signal; based on the different second subsequences and the corresponding current signals, a training set for the decoding model is determined; signals that cannot be decoded by the basic model can be annotated and included in the training set, thereby training a decoding model with higher accuracy.