504 results about "Bioinformatics analysis" patented technology

The invention provides a technical condition prediction method for a tunnel civil engineering structure, and relates to the technical field of traffic control monitoring systems.A biological acoustic composite sensing system comprising a distributed optical fiber acoustic sensing system and microorganism sample collection and analysis is constructed, and acoustic depth mode characteristics are mined by applying a deep learning model; the microbial dynamic biomarker is analyzed and identified by using bioinformatics; multi-modal information, a domain knowledge graph and a causal inference algorithm are fused, and a dynamic causal network model for revealing an internal driving relation in the degradation process is constructed; further, training and applying an adaptive neural network prediction model based on causal driving and fusing physical and biochemical mechanism constraints, and carrying out probabilistic prediction on future technical conditions of the tunnel; and executing anti-fact reasoning by using the causal network and the prediction model, and generating and optimizing an intervention strategy of cooperation of physical measures and biochemical measures. According to the method, the accuracy and advance of tunnel structure state prediction can be remarkably improved.

The invention discloses a protein optimization design and screening method and device based on an artificial intelligence algorithm, and the method takes fungal luciferase as an example, and integrates multi-dimensional bioinformatics analysis and deep learning technology to realize efficient protein engineering transformation and optimization. The method comprises the following steps: firstly, identifying a binding domain of luciferase and fluorescein by utilizing an AI-driven molecular docking simulation method, and determining a key conservative site by combining literature, evolutionary analysis and structural prediction; then, generating a protein functional domain skeleton under the constraint of a fixed site by adopting a diffusion model, and performing protein sequence prediction by utilizing a graph neural network model; and finally, scoring and screening the generated sequences to obtain high-stability candidate variants. According to the method, a conservative site dynamic fusion strategy is innovatively constructed, a fixed region is optimized through logic of structure prediction, evolution site intersection priority and literature site union set expansion, the diversity and adaptability of a protein design sequence are met, and the efficiency bottleneck of a traditional scheme is broken through.

The invention provides an individualized management system and method for colorectal cancer risk prediction, and relates to the technical field of medical diagnosis and individualized medical treatment. The system comprises a multi-omics data processing module used for collecting a blood sample of a subject, extracting circulating free DNA, and sequencing cfDNA by adopting a simplified methylation sequencing technology to obtain final original data of DNA methylation characteristics; the risk prediction module is used for carrying out bioinformatics analysis on the original data of the final DNA methylation features by adopting a machine learning algorithm, extracting a methylation feature set, a tail end motif feature set and a breakpoint motif feature set, and carrying out risk prediction on the basis of the extracted feature sets; and predicting the colorectal cancer disease risk of the subject by using a pre-trained prediction model to obtain a prediction result. The problem that the risk prediction accuracy of the colorectal cancer is low is solved.

The invention belongs to the technical field of gene engineering, and relates to a cyperus esculentus CeMYB154 gene capable of improving salt tolerance and active oxygen scavenging capacity and application of the cyperus esculentus CeMYB154 gene. The Cyperus esculentus CeMYB154 gene belongs to an MYB transcription factor family, the Cyperus esculentus CeMYB154 gene is screened and transformed into Arabidopsis thaliana through transcriptome sequencing, bioinformatics analysis, gene cloning, overexpression vector construction and recombinant strain overexpression, and analysis finds that under salt stress, compared with a wild type, the root length of a plant with the overexpressed CeMYB154 gene is obviously increased, the growth vigor is better, and the growth rate of the plant with the overexpressed CeMYB154 gene is higher. According to the present invention, the content of MDA and H2O2 is significantly reduced, and the activity of CAT, POD and SOD antioxidant enzymes is significantly enhanced, such that the overexpressed CeMYB154 gene can enhance the salt tolerance and the active oxygen scavenging ability of the plant, and the overexpressed CeMYB154 gene is proved to be the salt tolerance positive regulation factor; the CeMYB154 gene can be used in the field of salt-tolerant stress-resistant breeding of cyperus esculentus, and provides an important gene resource for salt-tolerant molecular breeding.

The invention relates to the technical field of bioinformatics, in particular to a biological information analysis system based on a large model technology, which comprises a data analysis calibration module, a problem disassembly module, an analysis task arrangement module, a result mapping module and a feedback iteration module. According to the method, genome comparison and clinical phenotype timestamps are dynamically calibrated, time sequence dislocation deviation is eliminated, base complementary pairing is combined with protein network anomaly screening, low-abundance collaborative variation capture is enhanced, genotype-phenotype discrete distribution quantifies and unifies multi-modal data benchmark, and the problem of multi-source heterogeneous standardization deficiency is solved; the method comprises the following steps: classifying and integrating pathogenic gene semantic weights by structural variation, balancing a statistical threshold and a biological function, dynamically optimizing an analysis sequence, synchronously covering a key mutation region, improving function annotation of a non-coding region, integrating gene expression clustering and protein network topology in a three-dimensional distribution manner, breaking through two-dimensional space limitation, performing closed-loop feedback to correct a threshold iteration elimination rule, and finally obtaining a high-quality gene expression cluster. And the genetic heterogeneity false positive rate is reduced.

A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline. Additionally, a second integrated circuit is also provided, where each second integrated circuit forming a field programmable gate array (FPGA), the FPGA being configured by firmware to arrange a set of hardwired digital logic circuits that are interconnected by a plurality of physical interconnects to perform a second set of genomic processing steps of the sequence analysis pipeline, the set of hardwired digital logic circuits of each FPGA being arranged as a set of processing engines to perform the second set of genomic processing steps. A shared memory is also provided.

The invention discloses a crested ibis habitat ecological quality trend analysis method and system, and relates to ecological quality monitoring. The method comprises the following steps: S1, constructing an intelligent sensing network, synchronously obtaining multi-source data of a habitat, identifying activity events of crested ibis, and generating a multi-dimensional habitat parameter table; s2, collecting environmental samples, and generating a microbial functional gene abundance matrix through metagenome sequencing and bioinformatics analysis; s3, taking the activity events of the crested ibis as behavior tags, and generating habitat function health indexes by coupling the parameter table and the matrix training machine learning prediction model; s4, performing spatial interpolation and trend analysis based on the habitat function health index to generate an ecological quality space-time evolution graph; and S5, based on the ecological quality space-time evolution graph, performing quantitative analysis by using a spatial differentiation statistical model, and generating a trend analysis report. By fusing multi-source data, real-time dynamic evaluation of habitat ecological quality and quantitative analysis of driving factors are realized, and a direct decision basis is provided for accurate protection.

The invention relates to the field of noninvasive prenatal diagnosis, and particularly discloses a preeclampsia noninvasive screening method based on deep sequencing 8bp oligonucleotide double-fragment characteristics, which comprises the following steps: collecting preeclampsia and healthy pregnant woman peripheral blood samples, and extracting free DNA for high-throughput sequencing; the method comprises the following steps: extracting core 8-mer sequences' GTGCGCCC 'and' GATGGGGT 'in a long fragment of 150-200bp through bioinformatics analysis; an integrated support vector machine, K-nearest neighbor, extreme gradient lifting, a random forest and a multi-layer perceptron are combined with a logistic regression element classifier to construct a stacking model, the frequency of a core sequence is normalized, machine learning analysis is carried out, and the preeclampsia risk is predicted. According to the invention, two 8bp oligonucleotide characteristic fragments are specifically screened, and a deep learning architecture of multi-model fusion is combined, so that the limitations of low specificity and invasive detection of a traditional screening method are effectively broken through.

The invention provides a food component analysis method and system based on a near infrared spectrum. The method comprises the following steps: acquiring a near infrared spectrum signal through a food sample, and generating a sample near infrared spectrum signal by adopting an intelligent sampling method; based on the near infrared spectrum signal of the sample, automatically focusing a key area by using an attention mechanism enhanced convolutional neural network, and combining a spectrum characteristic selection technology to screen spectrum characteristics, and generating sample component and content information; based on the sample component and content information, evaluating the human body metabolism influence degree by applying a gradient boosting decision tree algorithm, analyzing a biological mechanism by combining a bioinformatics analysis technology, and generating a sample influence evaluation report; and based on the sample influence evaluation report, adopting natural language processing to generate a food component analysis report. According to the technical scheme provided by the invention, high-precision and automatic food component analysis is realized, the analysis accuracy and efficiency are improved, and an influence mechanism of food components on human metabolism is deeply analyzed.

The invention discloses a novel coronavirus neutralizing antibody, a detection kit and application of the novel coronavirus neutralizing antibody. The amino acid sequence of a heavy chain variable region of the neutralizing antibody is shown as SEQ ID No.1, and the amino acid sequence of a light chain variable region of the neutralizing antibody is shown as SEQ ID No.2. The antibody with mature affinity is screened through bioinformatics analysis of a single B cell, the antibody screening process is optimized by combining single cell RNA sequencing, VDJ rearrangement analysis and somatic cell hypermutation research, blindness of a traditional method is avoided, and the accuracy and effectiveness of antibody screening are improved. According to the neutralizing antibody GR12 provided by the invention, a heavy chain variable region and a light chain variable region of the neutralizing antibody GR12 can be specifically combined with an RBD structural domain of the SARS-CoV-2 and an S-Trimer structural domain of an Omicro variant, so that a broad-spectrum neutralizing effect on the SARS-CoV-2 virus and the variant thereof is realized. The binding activity of the antibody GR12 to S-Trimer and RBD under 2-fold and 300-fold dilution conditions is obviously superior to that of other antibodies, which indicates that the antibody GR12 has high affinity and dilution stability and is suitable for clinical large-dose administration.

The invention relates to the technical field of nucleic acid detection, in particular to a product and a method for detecting bifidobacterium longum subsp. Longum 6-1. Bioinformatics analysis is carried out based on a whole genome sequence of the bifidobacterium longum subspecies longum 6-1, the primer pair and the primer probe combination are obtained through optimization, and the primer pair and the primer probe combination have good specificity and sensitivity in the aspect of detecting the bifidobacterium longum subspecies longum 6-1; the bifidobacterium longum subsp. Longum 6-1 and other strains (including other same subsp. Longum strains, other same strains and other strains) can be quickly and accurately distinguished, and the strain level quantitative detection of the strain in a complex biological sample (such as excrement) can be realized.

The invention provides a lung adenocarcinoma prognostic marker and a model, constructs a lung adenocarcinoma prognostic model based on mRNA and lncRNA related to programmed cell death (PCD), and synthesizes bioinformatics analysis and experiments to explore the biological effect of the lncRNA model in lung adenocarcinoma. The prognosis model covers all PCD pathways and various molecules, has stable prognosis prediction accuracy, and can provide a potential molecular target for personalized treatment. According to the method disclosed by the invention, the PCD-related mRNA and lncRNA are integrated to construct a lung adenocarcinoma diagnosis model suitable for Chinese population, so that the identification capability of tumor patient classification is enhanced from multiple aspects, the accuracy and reliability of prognosis prediction are improved, powerful support can be provided for promoting personalized treatment strategies of lung adenocarcinoma patients, and the method is suitable for popularization and application.

The invention discloses a novel coronavirus neutralizing antibody, a detection kit and application of the novel coronavirus neutralizing antibody. The amino acid sequence of a heavy chain variable region of the neutralizing antibody is shown as SEQ ID No.1, and the amino acid sequence of a light chain variable region of the neutralizing antibody is shown as SEQ ID No.2. The antibody with mature affinity is screened through bioinformatics analysis of a single B cell, the antibody screening process is optimized by combining single cell RNA sequencing, VDJ rearrangement analysis and somatic cell hypermutation research, blindness of a traditional method is avoided, and the accuracy and effectiveness of antibody screening are improved. According to the neutralizing antibody GR75 provided by the invention, a heavy chain variable region and a light chain variable region of the neutralizing antibody GR75 can be specifically combined with an RBD structural domain of the SARS-CoV-2 and an S-Trimer structural domain of an Omicro variant, so that a broad-spectrum neutralizing effect on the SARS-CoV-2 virus and the variant thereof is realized. The binding activity of the antibody GR75 to S-Trimer and RBD under 2-fold and 300-fold dilution conditions is obviously superior to that of other antibodies, which indicates that the antibody GR75 has high affinity and dilution stability and is suitable for clinical large-dose administration.

The invention relates to the technical field of bioinformatics analysis, in particular to an enhanced CT image-based hepatocellular carcinoma postoperative early recurrence multi-modal prediction model and a construction method thereof, and the construction method comprises the following steps: S1, data acquisition: collecting clinical data and liver enhanced CT images of a hepatocellular carcinoma surgical patient, and evaluating the recurrence condition of the HCC patient; s2, image preprocessing: sketching a region of interest in the image, and extracting deep learning features; s3, establishing a model: establishing a plurality of image omics models, constructing a plurality of deep learning models, and constructing a multi-modal model; s4, evaluating and verifying the model: evaluating the prediction accuracy of the multi-modal model by adopting an ROC curve and an AUC value, and evaluating the prognosis prediction capability of the patient by using a Kaplan-Meier curve; according to the method, the characteristic expression ability and the recurrence risk discrimination performance are improved, a scientific basis can be provided for follow-up visit and treatment of the hepatocellular carcinoma postoperative patient, and the lifetime of the patient is prolonged.

The invention discloses a novel coronavirus neutralizing antibody GR46, a detection kit and application of the novel coronavirus neutralizing antibody GR46. The amino acid sequence of a heavy chain variable region of the neutralizing antibody is shown as SEQ ID No.1, and the amino acid sequence of a light chain variable region of the neutralizing antibody is shown as SEQ ID No.2. The antibody with mature affinity is screened through bioinformatics analysis of a single B cell, the antibody screening process is optimized by combining single cell RNA sequencing, VDJ rearrangement analysis and somatic cell hypermutation research, blindness of a traditional method is avoided, and the accuracy and effectiveness of antibody screening are improved. According to the neutralizing antibody GR46 provided by the invention, a heavy chain variable region and a light chain variable region of the neutralizing antibody GR46 can be specifically combined with an RBD structural domain of the SARS-CoV-2 and an S-Trimer structural domain of an Omicro variant, so that a broad-spectrum neutralizing effect on the SARS-CoV-2 virus and the variant thereof is realized. The binding activity of the antibody GR46 to S-Trimer and RBD under 2-time and 300-time dilution conditions is obviously superior to that of other antibodies, which indicates that the antibody GR46 has high affinity and dilution stability and is suitable for clinical large-dose administration.

The invention provides a method for screening high-activity endogenous antibacterial peptides, which comprises the following steps: (1) collecting antibacterial peptide sequences in an antibacterial peptide database, and constructing an antibacterial peptide prediction model; (2) acquiring pig source proteome data; (3) screening out sequences with the length of 8-50 residues from pig-source proteome data to construct a candidate data set; (4) screening out non-redundant sequences from the candidate data set to construct a prediction data set; (5) predicting endogenous antibacterial peptides in the prediction data set by using the antibacterial peptide prediction model to obtain candidate antibacterial peptides; and (6) carrying out bioinformatics analysis on the candidate antibacterial peptide, comparing the candidate antibacterial peptide with an antibacterial peptide database, and screening out the antibacterial peptide with the similarity of less than 100% and secretory protein characteristics or exosome protein characteristics to obtain the high-activity endogenous antibacterial peptide. The method provided by the invention can be used for efficiently and quickly screening the high-activity endogenous antibacterial peptide, provides a new way for developing novel antibacterial peptide, and has a wide application prospect.

The invention relates to the field of cherry molecular biotechnology and molecular assisted breeding technology detection, in particular to a molecular marker for identifying the core SNP (single nucleotide polymorphism) of a Chinese cherry resource and a DNA (deoxyribonucleic acid) fingerprint spectrum database constructed by using marker sites. 185 resources representing the distribution and genetic diversity of Chinese cherries in China are utilized to perform whole genome re-sequencing and biological information analysis, 469776 SNP molecular markers are obtained, 1674 SNP molecular markers are screened out to serve as core SNP markers, and a DNA fingerprint database of cherry resources is constructed and can be used for identifying germplasm resources of Chinese cherries. DNA genetic information and genetic differences of the to-be-detected Chinese cherry resources are evaluated, and a scientific basis is provided for effective protection of the Chinese cherry resources, utilization of local germplasm and selection of cherry breeding.

The invention provides equipment, a method and a system for evaluating prognosis of cervical cancer, squamous carcinoma and adenocarcinoma and application of the equipment, the method and the system, and belongs to the technical field of medical evaluation. Two biomarkers, namely adenylate kinase 4 and cavernous malformation 2 protein, for evaluating prognosis of cervical squamous cell carcinoma and adenocarcinoma are obtained through multivariate statistical analysis, difference screening, COX regression analysis and other biosignal analysis methods. Based on the biomarker, evaluation equipment, a computer execution method, a computer system and the like for evaluating the prognosis of cervical squamous cell carcinoma and adenocarcinoma are constructed, and the evaluation equipment, the computer execution method, the computer system and the like are used for accurately judging the prognosis condition of a cervical cancer patient.

The invention provides a CsERECTA gene-based tea tree leaf shape regulation and control method and a tea tree light utilization rate improving method, which are characterized in that a sequence of a tea tree gene is cloned to obtain a complete sequence; then, the CsERECTA is subjected to bioinformatics analysis, expression of a GUS reporter gene is started by constructing a plant expression vector and connecting a target fragment, and a recombinant plant vector is used for genetic transformation of tobacco, so that the function of the CsERECTA is verified; the character of the CsERECTA transgenic line is analyzed, the leaf shape is determined, the method capable of improving the leaf shape of the tea tree is obtained, and a foundation is laid for cultivating a new variety and improving the light utilization rate of the tea tree by using the CsERECTA gene.

The invention discloses a targeted sequencing method for various pathogenic microorganisms. The targeted sequencing method specifically comprises the following steps: collecting a biological detection material containing the pathogenic microorganisms; extracting nucleic acid in the pathogenic microorganisms to be detected; designing specific primers and probes according to the target pathogenic microorganisms; amplifying a nucleic acid sequence through a PCR (Polymerase Chain Reaction) technology; carrying out deep sequencing based on a high-throughput sequencer; according to the present invention, the specific primers and the probe are designed, such that the nucleic acid sequence of the target pathogenic microorganism can be efficiently enriched, and the high-throughput sequencing technology is adopted to perform the deep sequencing so as to significantly improve the sensitivity and the accuracy of the detection of the plurality of pathogenic microorganisms; the method can be used for simultaneously detecting various different types of pathogenic microorganisms such as bacteria, viruses, fungi and the like, is simple and convenient to operate, short in time consumption and low in cost, and can provide powerful support for quickly and accurately identifying the pathogenic microorganisms and timely taking effective prevention and control measures.

The monoclonal antibody of the glycoprotein Gn of the severe fever with thrombocytopenia syndrome virus is screened on the basis of immune repertoire sequencing, and the biological characteristics of the monoclonal antibody are identified. The method comprises the following steps: taking purified SFTSV-Gn as bait, taking virus specific B cells from an immunized female BALB / c mouse B cell bank, selecting an antibody sequence with potential binding activity by utilizing a 10 * immune repertoire sequencing method in combination with bioinformatics analysis, constructing the antibody sequence to an eukaryotic expression vector pcDNA3.4, expressing and purifying a monoclonal antibody, and identifying the biological activity of the monoclonal antibody. 14 antibodies are selected from 3544 captured B cells, functional verification shows that 12 antibodies can be combined with SFTSV-Gn glycoprotein, and the Gn-5 antibody and the Gn-7 antibody have high combining capacity; western blot, indirect immunofluorescence test and flow cytometry prove that the antibody can specifically recognize the SFTSV, the effective concentration is as low as 2 mu g / mL, and a foundation is laid for development of a rapid diagnosis reagent for the SFTSV.

The invention relates to a hepatocellular carcinoma gene knockout target library based on multiple omics and a screening method of the hepatocellular carcinoma gene knockout target library, and the gene knockout target library for precise treatment of hepatocellular carcinoma is finally obtained through data collection and integration, data screening and target verification in sequence. According to the invention, through multi-omics data integration and bioinformatics analysis, key driving genes of hepatocellular carcinoma are systematically screened, and the important effects of the genes in occurrence, development, metastasis, drug resistance and immune escape of hepatocellular carcinoma are disclosed; the genes not only deepen the understanding of the hepatocellular carcinoma molecular mechanism, but also provide important theoretical basis and potential intervention targets for the development of targeted therapy and personalized therapy strategies.

The invention belongs to the technical field of biological medicine and molecular biology, and particularly relates to application of circ0005704 and related biological elements thereof in diagnosis and treatment of recurrent spontaneous abortion with unknown reasons. Researches find that differential expression and autophagy level of ULK1 in trophoblast cells of URSA patients are increased. High-throughput transcriptome sequencing is combined with bioinformatics analysis, and it is found that miR-26a-5p is down-regulated in URSA patients, is responsible for up-regulation of ULK1 and promotes autophagy of trophoblast cells, so that occurrence of URSA is increased. Through a high-throughput transcriptional set screening strategy and dual luciferase reporter gene analysis, it is found that circ0005704 enhances the expression of ULK1 through miR-26a-5p. In a word, the research of the invention shows that the circ0005704 / miR-26a-5p / ULK1 signal axis participates in the pathogenesis of URSA by adjusting the migration of the trophoblast cells, and a new target and scientific evidence are provided for the clinical treatment of URSA.

The invention discloses a method for screening a Wilson disease serum exosome miRNA biomarker based on a transcriptomics technology, and belongs to the field of bioinformatics analysis of diseases. According to the invention, the effect of miRNA in WD pathogenesis is discussed by identifying serum exosome miRNA, and a potential biomarker is provided for accurate diagnosis and treatment of the disease. According to the invention, 59 DE-miRNAs are identified by analyzing the expression of differential miRNAs of WD and control group patients, and the DE-miRNAs are related to key approaches such as metabolic regulation, cancer progression, signal transduction and the like. Besides, the reliability of the key DE-miRNA, including miR-451a, miR-204-5p and the like, is confirmed through experimental verification, and the potential of the key DE-miRNA as a non-invasive biomarker is indicated. Research results provide important theoretical basis and new insight for accurate diagnosis of WD and development of potential therapeutic targets.

The present invention provides a quality control analysis method for third-generation sequencing, which includes performing raw sequencing on the extracted gene sequence to obtain a POD5 text of the initial data. The POD5 text is then converted into a FASTQ file, and adapter data is removed. Quality assessment is then performed to obtain read data. The read data is then aligned and analyzed with the target base sequence of theoretical length, impurities are filtered, and finally, visual detection results are obtained. The present invention also provides a gene extraction method, which forms a highly optimized and reliable bioinformatics analysis process from raw data acquisition, preprocessing, quality assessment, alignment analysis, to final report generation.

The invention provides a new bunyavirus neutralizing antibody screening method based on single cell BCR sequencing. The new bunyavirus neutralizing antibody screening method comprises the following steps: S1, collecting peripheral blood B cells of acute stage and recovery stage patients and healthy volunteers of new bunyavirus infected persons; s2, carrying out CD19 < + > CD38 < + > CD138 < + > magnetic bead separation to obtain a single-cell suspension; s3, constructing a single cell transcriptome and a BCR library, separating single cells by using a microfluidic system, and performing high-throughput sequencing; s4, analyzing a B cell subset, a BCR cloning amplification mode and a VJ gene pair enrichment characteristic through bioinformatics analysis; and S5, screening a specific BCR clone type related to the severity of the disease as a neutralizing antibody candidate target. The method provided by the invention provides powerful support for immune monitoring and vaccine design of new bunyavirus infection, and is expected to provide new strategies and methods for clinical treatment and prevention.

The invention discloses an application method for revealing RIPK3 as a pathological index of osteoarthritis based on transcriptomics analysis, and belongs to the technical field of molecular biology and genetic engineering.The method comprises the following steps that S1, a Trizol reagent is used for conducting total RNA extraction on an articular cartilage specimen, and the RIN number gt is selected; 7.0, constructing a sequencing library by using the high-quality RNA sample; s2, carrying out quality inspection on the constructed library, and carrying out mRNA sequencing by using an Illumina NovaseqTM6000 sequencer after all the libraries are qualified in quality inspection; s3, carrying out bioinformatics analysis on data generated by high-throughput sequencing; s4, different parts of the cartilage tissue of the OA patient are labeled with RIPK3 through immunofluorescence, it is proved that expression of the RIPK3 in cartilage cells has strong correlation with the pathology of the OA focus, and the feasibility of taking the RIPK3 as a clinical pathology index is proved.

The invention belongs to the technical field of tumor molecular diagnosis and biological information analysis, and relates to a high-throughput sequencing method and system for monitoring acute lymphocytic leukemia (MRD). Through targeted sequencing with a unique molecular identifier and / or a double-chain tag, error modeling based on a background noise spectrum and statistics / machine learning pseudo variation filtering, ultra-deep accurate detection of IG / TCR cloning and related gene low-frequency variation is realized. And an artificial intelligence recurrence risk prediction model is established by combining a time sequence MRD index, cloning diversity and clinical information, and a structured clinical report is output and docked with LIS / HIS. According to the method, the sensitivity and the specificity of ALL minimal residual disease detection can be remarkably improved, dynamic evaluation on leukemia cloning evolution and recurrence risks is realized, and a reliable basis is provided for individualized treatment decision and long-term follow-up visit.

The invention relates to the technical field of biology, and provides a molecular marker for identifying maize varieties, which comprises 40 pairs of marker primers designed based on 40 SSR sites in the national standard of maize. The distribution of the molecular markers on the whole genome is completely consistent with the distribution of 40 national standard SSR sites of corn, and each chromosome corresponds to 4 pairs of markers on average. The invention also provides a development method and application of the molecular marker. According to the invention, through innovative means such as deep primer optimization and comprehensive sequence retrieval, the problem of dimer formation is ingeniously avoided, and 40 pairs of labeled primers are successfully developed and designed; based on the primers, by means of multiple PCR amplification, sequencing library construction, sequencing, biological information analysis and the like, the actual application requirements of corn variety authenticity identification, purity detection, germplasm resource identification and the like can be met; meanwhile, the method has the characteristics of low cost, simplicity in operation, high flux, high sensitivity and the like.

The invention discloses a sparse auto-encoder-based cell type deconvolution modeling method and system, and relates to the technical field of artificial intelligence technology and bioinformatics. Single cell RNA sequencing data is input into a trained sparse auto-encoder model to obtain a predicted cell type; the sparse auto-encoder model training process comprises the following steps: generating simulated bulk transcriptome data by using single-cell RNA sequencing data to construct a training set; constructing a sparse auto-encoder model, simulating bulk transcriptome data, generating a predicted cell type proportion through an encoder, and generating reconstructed bulk transcriptome data through a decoder according to the predicted cell type proportion; constructing a total loss function based on the KL divergence function, the reconstruction error and the prediction error so as to optimize trainable parameters in the sparse auto-encoder model; according to the deconvolution modeling method and system, the problems of low cell type prediction accuracy and low algorithm efficiency in the prior art are solved, and rapid and efficient bioinformatics analysis is realized.