231 results about "Genome sequence analysis" patented technology

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.

Provided herein are technologies for framing and evaluating biological sequence-based analysis tasks in a unified, natural-language-based, text in and text out format. Among other things, methods and systems of the present disclosure provide machine-learning technologies for combining biological sequence data, representing, for example, DNA, RNA, and protein sequences, with natural language, conversational style prompts that set out particular analysis tasks to be performed on the biological sequence data. This approach, for example, allows complex analysis tasks, including, but not limited to, identification of various sequence modifications, genes, and regulatory elements in DNA sequences, and quantification of properties such as degradation propensity of RNA and protein stability, to be input to a machine learning model in a uniform text-based format and for output to be generated in a same, unified, text-based format.

The present invention discloses a combination of different nucleic acid aptamers with 291 known targets. By performing sequencing analysis on the nucleic acid aptamer sequences of this combination through single-cell high-throughput sequencing technology, a cell atlas targeting mononuclear cells derived from the peripheral blood of patients with cholangiocarcinoma can be constructed. The nucleic acid aptamers covered by this combination have high specific affinity for their molecular targets. After extending adapters commercialized for sequencing platforms at both ends of the nucleic acid aptamer sequences respectively, by performing high-throughput sequencing on the nucleic acid aptamer sequences with sequencing adapters bound to the surface of mononuclear cells, high-throughput analysis of biomarkers on the surface of mononuclear cells derived from the peripheral blood of patients with cholangiocarcinoma can be achieved, thereby constructing a cell atlas of mononuclear cells derived from the peripheral blood of cholangiocarcinoma.

The invention discloses a semantic intelligent enhanced DNA storage method for the Internet of Things, and belongs to the crossing field of artificial intelligence and biological information storage, the compression efficiency and robustness of DNA image storage are effectively improved through introduced semantic extraction and a multi-read screening mechanism of design, key information areas in images are extracted through semantic extraction, and the compression efficiency and robustness of DNA image storage are improved. The method has the advantages that redundant backgrounds are eliminated, coding lengths are reduced, high-quality sequences are selected from sequencing copies by the aid of scoring and sequence analysis through a multi-read screening mechanism, fault tolerance is enhanced, the method is applicable to efficient semantic storage in scenes of the internet of things, the problem of low storage efficiency due to excessive redundant information in original images in existing DNA image storage methods is solved, and the method is applicable to high-efficiency semantic storage in scenes of the internet of things. And a high bit error rate exists in the DNA synthesis and sequencing process, so that the image recovery quality is influenced.

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 the technical field of flow calibration, and discloses a multi-pipeline flow collaborative calibration system. The system comprises a flow characteristic acquisition module, a flow category classification module, a sequence analysis module, a trend analysis module, a correction module and a collaborative decision module. The flow characteristic acquisition module is used for acquiring current flow data and real-time characteristic information of multiple pipelines and indexing a historical flow data set; the traffic category classification module classifies the historical characteristic information to obtain a plurality of traffic categories, and extracts related information for processing to obtain a historical calibration score set; the sequence analysis module serializes the historical calibration score set and ranks the historical calibration score set according to time to form a historical traffic sequence; the trend analysis module analyzes the flow change rate and the stability deviation rate according to the historical flow sequence; the correction module matches the real-time characteristic information with the traffic category, and corrects the rate value according to the deviation; and the collaborative decision-making module performs multi-pipeline collaborative calibration decision-making based on the corrected data, generates and executes a flow calibration scheme, and assists the multi-pipeline system in precise flow control.

The present invention discloses a black chicken liver hydrolyzed peptide that can be used to improve ulcerative colitis, and its preparation method and application, which belong to the field of biomedicine technology. The preparation method of the black chicken liver hydrolyzed peptide comprises the following steps: making black chicken liver into minced meat and mixing it with water, heating the obtained liquid material, adding alkaline protease for enzymatic hydrolysis, inactivating the enzyme and collecting the supernatant by centrifugation, and freeze-drying to obtain the black chicken liver hydrolyzed peptide. The present invention adopts formaldehyde titration to detect the degree of hydrolysis, adopts SDS-PAGE electrophoresis and Tricine-SDS-PAGE electrophoresis to detect the molecular weight, performs sequence analysis by LC-MS / MS, uses a database to predict the biological function of peptide segments, detects the antioxidant and blood pressure lowering ability of black chicken liver peptide by in vitro experiments, and detects the effect of black chicken liver peptide in improving colitis by mouse experiments. The results show that the black chicken liver peptide prepared by the present invention has the advantages of antioxidant, blood pressure lowering and improvement of ulcerative colitis.

The invention relates to a privileged account-oriented dynamic authority control and behavior auditing method and system, which integrate operation sequence analysis, environmental threat intelligence and user behavior baselines, construct a behavior DNA model and realize accurate real-time risk scoring. A transient dynamic token is adopted to realize permission minimization, a token fusing mechanism is initiated to realize real-time interruption of high-risk operation, suspicious operation intention verification is performed through a mirror image sandbox, and a virtual pressure test is introduced to actively detect potential threats. A full-link digital twin system is established, it is ensured that auditing records cannot be tampered in combination with a distributed consensus auditing account book, and attack chain visualization and operation scene accurate playback are supported. According to the scheme, the problems of permission flooding, extensive management and control, weak auditing and the like existing in traditional privileged account management are effectively solved, precise management and control, intelligent early warning and credible traceability of privileged behaviors are realized, and comprehensive protection is provided for organizing core assets.

The invention relates to the technical field of physiological signal analysis, in particular to a sleep disorder intelligent diagnosis system based on a multi-modal knowledge graph, which comprises a signal lag analysis module, an abnormal signal identification module, a graph construction module, a graph path generation module and a diagnosis result output module. According to the method, difference comparison and normalized sequence analysis in a time window are performed on multiple types of physiological response data, and derivative trend identification and mutation section calibration are combined, so that collaborative identification of signal delay response and abnormal change positions is realized, and multi-dimensional information of duration, frequency and fluctuation amplitude in abnormal events is further structured; the method comprises the following steps: constructing a traceable symptom expression vector, extracting structural features of the traceable symptom expression vector in a time sequence evolution process through a cross-time window entity evolution path, identifying a growth trend of association strength between symptoms according to an attribute change direction and a path connection mode, and judging a fluctuation mode and an abnormal evolution tendency of a sleep state of a user in a specific time period.

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 dynamic multi-modal biological sequence staged pre-training system for precise breeding, which comprises a multi-modal data organization unit used for collecting a single-modal sequence, generating a two-modal pairing sequence, constructing a three-modal interpenetrating sequence and simulating biological information transmission; the unified sequence representation unit is used for performing unified word segmentation on each modal sequence and adding modal marks; the progressive pre-training strategy unit is used for training in three stages and dynamically adjusting the modal mixing proportion in combination with a simulated annealing strategy; the cross-modal autoregression unit realizes prediction conversion between modals; the sequence feature extraction and prediction unit is used for obtaining a quantitative prediction value. The invention further provides a dynamic multi-mode biological sequence staged pre-training method for precise breeding. Therefore, the biological sequence feature prediction precision can be remarkably improved, the training convergence speed is increased, the performance equivalent to that of a large model is achieved, the cost is low, flexible deployment in various environments can be achieved, and efficient, accurate and low-cost technical support is provided for biological sequence analysis.

Disclosed herein are sequencing systems and sequencing methods for training neural networks and for utilizing the trained neural networks for sequencing analysis after acquiring flow cell images using the sequencing systems. The sequencing systems disclosed herein can include Field-Programmable Gate Array (FPGAs), artificial intelligence (AI) chips, or a combination thereof.

The invention is suitable for the technical field of gene sequencing, and provides a nanopore sequencing signal identification method and system based on Transform, and the method comprises the following steps: carrying out normalization processing on a nanopore sequencing signal, and segmenting the nanopore sequencing signal into signal windows with fixed lengths; signal features are extracted through a Transformer encoder comprising a convolutional layer and a multi-head self-attention module; generating a prediction probability of a current base through a cross attention mechanism by adopting an autoregressive Transform decoder and combining the signal features and context information of a decoded base sequence; iteratively generating an optimal base sequence based on a beam search algorithm, and optimizing decoding efficiency in combination with key value cache; and carrying out overlapping region fusion and quality control on a segmented decoding result, and outputting a final sequence. According to the method, the precision and reliability of nanopore sequencing in complex biological sequence analysis are remarkably improved, and the recognition accuracy on multiple gene sequencing data sets is higher than that of an existing CTC-based model.

The invention discloses a method for detecting accessibility of space chromatin and application of the method. The method comprises the following steps: (1) slicing a tissue sample to be detected on a chip with spatial information; (2) fixing, permeabilizing and dyeing a tissue sample to be detected; (3) preparing fragmented genome DNA (deoxyribonucleic acid); (4) performing DNA hybridization based on a transfer mode; (5) carrying out connection and terminal repair reaction on the fragmented genome DNA by using DNA polymerase and DNA ligase; (6) denaturation and melting; and (7) sequencing. According to the method, the transcriptional activity state of chromatin can be reflected through chromatin accessibility sequencing analysis, staining imaging and chromatin accessibility information can be obtained on the same tissue slice at the same time without complex micro-fluidic equipment, experimental operation is easy, repeatability is high, and the analysis result is more remarkable.

The invention belongs to the technical field of antibody preparation, and particularly relates to an anti-CD38 nano antibody as well as a preparation method and application thereof. The method comprises the following steps: constructing and expressing CD38 antibody protein, immunizing alpaca, obtaining immune alpaca PBMC (peripheral blood mononuclear cells), extracting RNA (ribonucleic acid) of the cells, carrying out reverse transcription to obtain cDNA (complementary deoxyribonucleic acid), carrying out PCR (polymerase chain reaction) to obtain antibody gene segments, constructing the antibody gene segments on a phage expression vector to construct a CD38 immune antibody library, carrying out two rounds of panning, carrying out Clone ELISA (enzyme-linked immuno sorbent assay) detection on clones to obtain an antibody combined with the CD38 protein, carrying out sequencing analysis, and selecting a unique sequence. High-throughput expression is carried out through a mammalian cell high-throughput expression system, antibody protein is obtained, FACS detection is carried out through a CD38 high-expression cell line, and finally the antibody combined with CD38 is obtained. The method is simple and rapid to operate, a mammalian cell expression system induces efficient expression of the antibody, processing modification can be performed after translation, and the activity of the antibody is closer to that of a natural antibody.

The application discloses a high-sweetness-amino-acid-content Flammulina velutipes variety and a MNP molecular identification method and application thereof. The Flammulina velutipes variety has excellent properties, the cap is not easy to open, the content of sweet amino acids is high, the diversified market demand is met, the factory annual bottle cultivation is suitable, and the Flammulina velutipes variety has a good application and popularization prospect. The MNP molecular fingerprint of the Flammulina velutipes variety 'Shangyan A111' is comprehensive multiple amplification and sequencing technology, sequence analysis of all marker sites of multiple samples can be performed at one time, compared with ISSR, RAPD, SSR and other molecular markers and mushrooming test, the MNP molecular fingerprint has the advantages of high throughput, multi-target, high sensitivity and high precision. The MNP molecular fingerprint of the Flammulina velutipes variety 'Shangyan A111' has specificity and specificity in identifying the Flammulina velutipes strain 'Shangyan A111'.

This invention belongs to the field of biodetection technology, specifically relating to a monoclonal antibody combination for detecting the N protein of porcine reproductive and respiratory syndrome virus (PRRSV) and its application. The combination consists of monoclonal antibodies 1D7 and 5C7. Sequence analysis has clarified the CDR amino acid sequences of the heavy and light chain variable regions, as shown in SEQ ID NO.1-SEQ ID NO.12, and a double-antibody sandwich ELISA detection method has been established based on this. This method uses 1D7 as the coating antibody and 5C7 as the labeling antibody, achieving a sensitivity of up to 100 pg / mL, high specificity, no cross-reactivity with irrelevant antigens such as PEDV, and effectively detecting the N protein in PRRSV vaccine strains such as JXA1-R and R-98. This invention can be used for rapid detection of PRRSV antigen in clinical samples and for vaccine quality control.

The application provides a bidding full-element compliance review method for multi-modal model space-time sequence analysis, relates to the technical field of data processing, and comprises the following steps: acquiring space-time sequence data and auxiliary data of a bidding project, constructing a space-time double-flow feature network, constructing a knowledge graph based on output, calculating an abnormal score by using a space-time mode encoder, optimizing an abnormal detection result by using a graph attention network, and dynamically generating a bidding compliance verification path by using deep reinforcement learning. The application can realize comprehensive analysis of bidding data, improve the accuracy of abnormal behavior detection, reduce the cost of manual review, and optimize the efficiency of the verification path.

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 application discloses a PCR primer pair and a molecular marker probe for distinguishing between barnyard grass and rice, a detection kit and application thereof. After align analysis on chloroplast genome sequences of the barnyard grass and the rice, it is found that a difference site exists in a 91 kb region, sequences of the upstream and downstream of the difference site are taken as reference sequences to select homologous sequences to design primers for PCR amplification, and the amplification result proves that the difference site fragment obtained by chloroplast genome sequence analysis exists and can be amplified and identified subsequently; the PCR amplification product is sequenced, and the sequencing result is compared to find that a 12 bp insertion site exists in the site and can separate the barnyard grass from the rice, a colloidal gold probe is designed according to the insertion site, and a RPA detection kit and a detection method are established, and the RPA detection kit is used to detect the barnyard grass and the rice, and the barnyard grass and the rice can be accurately distinguished.

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.

Sequencing methods for sequencing populations of nucleic acid molecules in which sequencing reads of amplicons are grouped into families according to the nucleic acid molecule of origin by partitioning, sample indexes and information from the sequencing reads, such as start and end points. The methods described herein provide many advantages over other sequencing analysis methods, including the identification of sequencing reads deriving from the same nucleic acid in the original sample while minimizing the number of aliquots that are processed.

The application belongs to the technical field of network security, and provides a security defense method, system and equipment based on behavior sequence analysis, which comprises data preprocessing and feature engineering, abnormal sample expansion under privacy protection, complex attack correlation detection and model dynamic optimization; the method generates a conditional sequence of an adversarial network through local training of each node under a federal learning framework, generates a compliant time sequence abnormal sample under the premise of protecting data privacy, effectively solves the problem of insufficient model training caused by the scarcity of abnormal samples, improves the generalization ability of the detection model, models each domain behavior sequence as a graph structure, and introduces a causal attention mechanism, so that the application can identify complex attack chains across resources and time periods, such as the whole process of APT attacks, and significantly improves the detection ability of attack behaviors with strong concealment and long duration.

The application provides a molecular marker related to sheep growth traits and application thereof, the molecular marker is designed by primers according to the sequence of the LGALS3 gene, DNA is extracted from sheep blood, and through PCR amplification, DNA sequencing and sequence analysis, it is found that a T / C polymorphism site exists at the 298th position of the amplified fragment, further, the polymorphism site of 849 Hu sheep is detected by using AQP primers, a least square model is established, genotype and growth traits are associated, finally, it is determined that Y at the 298th bp of the amplified LGALS3 gene fragment shown in SEQ ID NO. 1 is T or C, the mutation leads to T / C polymorphism of the molecular marker, and the molecular marker can be used as a molecular marker related to sheep growth traits. The molecular marker of the application can be used for screening a new variety of fast-growing high-quality mutton sheep, and can be used for screening assisted breeding, cultivating fast-growing sheep, and helping to increase economic benefits.

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 relates to the technical field of automatic interface detection, in particular to an automatic interface detection platform. According to the method, incompatible operations in a user operation sequence are accurately identified by constructing a dynamic conflict detection matrix and combining a characteristic value and singular value analysis technology, so that inconsistent system states or wrong operations are effectively avoided, the reliability of interface detection is guaranteed from the source, and the system fault risk caused by operation conflicts is reduced; according to the detection parameter intelligent optimization technology based on the genetic algorithm, the detection accuracy is maximized while the detection time is minimized, manual intervention is reduced, the interface detection efficiency and adaptability are remarkably improved, and the method is particularly suitable for a complex and changeable interface environment; according to the method, deep mining is carried out on the interface abnormal event through the LSTM time sequence prediction model, an operable diagnosis report is generated in combination with time standardization and sequence analysis, the performance attenuation trend of the interface is predicted, and long-term stability of data interaction is guaranteed.

The invention belongs to the technical field of biological medicines, and particularly relates to an anti-CD22 nano antibody as well as a preparation method and application thereof. The anti-CD22 nano antibody comprises a framework region and a complementarity determining region, wherein the complementarity determining region comprises CDR1 (SEQ ID NO: 1), CDR2 (SEQ ID NO: 2) and CDR3 (SEQ ID NO: 3). The preparation method comprises the following steps: immunizing alpaca by using Human CD22 / His protein, extracting RNA (Ribonucleic Acid) from PBMC (Peripheral Blood Mononuclear Cell) and reversely transcribing into cDNA (Complementary Deoxyribose Nucleic Acid), constructing a phage display library, then performing CD22 antigen protein elutriation to obtain positive clone, and after sequencing analysis, expressing the antibody by using a mammalian cell expression system. The optimized phage display technology is adopted, the screening period is short, and the obtained nano antibody is small in molecular weight, stable in structure and high in affinity to CD22. The antibody can be efficiently expressed through mammalian cells, and natural modification activity is reserved.

Disclosed herein are system, apparatus, method, and / or computer program product embodiments, and / or combinations and sub-combinations thereof which enables 3D base calling using flow cell images of samples such as in situ cells or tissue to ensure accurate base calling and sequencing analysis of 3D samples. Embodiments of the methods, systems, and media for 3D base calling of flow cell images includes image intensity, location, size, and / or of clusters or polonies to be relied on for accurate base calling.