4214 results about "Genome" patented technology

The invention belongs to the technical field of medical data processing and artificial intelligence, and particularly relates to a cardiovascular disease risk prediction system based on multi-modal fusion, which comprises a multi-modal data acquisition and preprocessing module, a cross-modal association graph construction module, a dynamic fusion and prediction module based on a graph neural network and an interpretability analysis module. By constructing a heterogeneous graph fusing prior knowledge and data driving and utilizing a graph attention network to perform multi-level dynamic feature fusion, deep integration and interaction of multi-modal data such as genomes, iconography, clinical and intestinal flora metabolism are realized, so that the accuracy and interpretability of cardiovascular disease risk prediction are improved.

The invention provides an enhancer RNA (Ribonucleic Acid) molecule MZGAe1 and application thereof, and relates to the technical field of biology. The invention provides an enhancer RNA (Ribonucleic Acid) molecule MZGAe1. The nucleotide sequence of the enhancer RNA molecule MZGAe1 is as shown in SEQ ID NO: 1; meanwhile, the invention further provides a specific sgRNA sequence for activating the molecule in a targeted manner and a recombinant vector of the specific sgRNA sequence. Expression of endogenous MZGAe1 of cells is specifically activated by adopting a CRISPR activation technology, and conversion of mouse embryonic stem cells to bicellular-like cells can be efficiently promoted. By providing a brand-new endogenous targeted MZGAe1 accurate activation tool, the efficient transformation of wild mouse embryonic stem cells to bicellular cells can be realized only under the condition of endogenous activation of single enhancer RNA molecule MZGAe1, the proportion is at least increased by 5%, the expression of a totipotent marker gene ZSCAN4 is activated, and the expression of the totipotent marker gene ZSCAN4 is promoted. And an efficient and specific brand-new research tool and scheme are provided for researching zygote genome activation, embryonic development early events and cell reprogramming.

The invention relates to the technical field of plant breeding, in particular to a molecular marker related to oil content and protein content of soybean and application of the molecular marker. The molecular marker is constructed on the basis of SNP sites; based on a genome version number Wm82. A2. V1, the SNP site is located at the 8605814th site of the No.8 chromosome of the soybean, and the polymorphism is A / G. The application comprises the following steps: (1) predicting or detecting the oil content or protein content of soybeans; (2) identifying or cultivating soybean varieties with high oil content or protein content; (3) soybean molecular marker assisted breeding; (4) soybean variety improvement related to oil content or protein content; and (5) soybean germplasm resource improvement. The molecular marker related to the soybean oil content and the protein content is obtained through research and screening, and the molecular marker can be applied to cultivation of soybean varieties with high oil content and high protein content and has important value in the field of soybean breeding.

The invention relates to a product of an SNP (Single Nucleotide Polymorphism) molecular marker related to sow litter size character detection and application of the product. The SNP molecular marker comprises Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt The nucleotide sequence of the gene is shown as SEQ ID No.1, and the nucleotide sequence of the gene is shown as SEQ ID No.1. The product at least comprises an upstream primer and a downstream primer, the nucleotide sequence of the upstream primer is as shown in SEQ ID No.2, and the nucleotide sequence of the downstream primer is as shown in SEQ ID No.3. The SNP molecular marker provided by the invention can be used for breeding, breeding and evaluating multi-variety sows with high reproductive performance.

The invention discloses an electric power infrastructure line operation behavior intelligent identification method, and belongs to the technical field of mode identification and data processing, and the method comprises the steps: constructing a heterogeneous space-time scene map, and carrying out the multi-modal structural perception of an operation site; segmenting the continuous behavior flow into behavior primitives in an unsupervised manner, and encoding the behavior primitives into observation sequences; analyzing the security operation regulations offline and compiling the security operation regulations into normal form behavior genomes; performing local sequence alignment on the observation sequence and the normal form genome to quantify behavior deviation; and identifying a jump critical point of the risk state based on the deviation disturbance and generating a structured early warning event. According to the method, a heterogeneous space-time scene map is constructed to fuse multi-modal perception data, an actual operation behavior is abstracted into an observation behavior primitive sequence, and the observation behavior primitive sequence and a normal form behavior genome compiled from a safety regulation are subjected to sequence alignment, so that behavior deviation can be quantified, a jump critical point of a risk state can be identified, and the accuracy of the risk state is improved. And accurate and foresight intelligent identification and early warning of operation behaviors are realized.

The invention is applicable to the technical field of clinical medicine, provides a clinical multi-modal cancer drug response prediction method based on feature reconstruction, constructs a clinical multi-modal model for drug response prediction of diffuse large B-cell lymphoma, and aims to predict the drug response of diffuse large B-cell lymphoma by integrating gene sequencing and clinical multi-modal data. And accurate drug reaction prediction is realized. The model adopts an end-to-end multi-stage processing flow: firstly, extracting gene features through TransP-Net, and processing multi-modal clinical data by using a clinical information encoder; then, pseudo-gene features are generated through a clinical-genome filling module to deal with the data missing problem; and finally, multi-modal deep fusion is realized through a clinical information decoder, and a prediction result is output. According to the method, data characteristics and working processes in a real clinical environment are fully considered, two conditions of complete gene data and missing gene data can be processed at the same time, and the method has a good clinical transformation prospect and application value.

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 discloses a molecular marker related to thousand seed weight of wheat, a detection primer and application of the molecular marker and the detection primer, and belongs to the technical field of molecular marker-assisted breeding. The nucleotide sequence of the molecular marker TaDTX50-STS is as shown in SEQ ID NO. 1; basic groups from the 502 site to the 661 site of the sequence as shown in SEQ ID NO. 1 have insertion / deletion mutation. The InDel molecular marker related to the thousand seed weight character in a wheat genome is identified and named as TaDTX50-STS, and by detecting the polymorphism or genotype of the InDel molecular marker, the InDel molecular marker can be used for identifying or assisting in identifying the thousand seed weight character of wheat, assisting in breeding dominant varieties with high thousand seed weight of wheat and improving the wheat breeding efficiency.

Disclosed herein are methods and systems of determining a cancer status or an organ health status of a subject, the method comprising: obtaining a biological sample obtained or derived from the subject; enriching a population of cells in the biological sample, wherein the population of cells comprises stem cells and / or progenitor cells; extracting nucleic acids from the enriched population of cells; assaying the extracted nucleic acids to generate at least one of a transcriptomic profile of the subject, a genomic profile of the subject, and / or an exomic profile of the subject; computer processing the at least one of the transcriptomic profile of the subject, the genomic profile of the subject, and / or the exomic profile of the subject; and determining, based at least in part on the computer processing, the cancer status or the organ health status of the subject, wherein the cancer status or the organ health status comprises a presence or an absence of an organ and / or a tissue impacted by the cancer or impacted by a disease, disorder, or condition.

The invention discloses a biomarker for evaluating litchi quality and a detection method, and relates to the technical field of biology. The marker is an SNP (Single Nucleotide Polymorphism) molecular marker, and the nucleotide sequence of the marker is as shown in SEQ ID NO.1-3. The molecular marker disclosed by the invention can be used for evaluating the quality of litchis, particularly evaluating the fructose content. Meanwhile, when the gene is applied to molecular marker assisted selection (MAS) and genome selection (GS), the genetic improvement progress of the litchi variety can be accelerated.

The invention provides an SNP (Single Nucleotide Polymorphism) site combination for genetic typing of micropterus salmoides and application of the SNP site combination. The SNP locus combination comprises 50000 SNP loci, and the positions and base information of the 50000 SNP loci on chromosomes are as shown in a table 3. By applying the micropterus salmoides whole genome liquid chip of the SNP site combination for genotyping of micropterus salmoides, provided by the invention, the genotype of a sample to be detected can be rapidly and accurately detected, and the average detection rate of the SNP sites and the average consistency rate of the genotype of the sample are as high as 99.95%; the micropterus salmoides whole genome liquid phase chip has the characteristics of high capture specificity, low cost, flexible sites and the like, is suitable for character breeding and improvement, gene mining, genetic relationship identification, genetic diversity analysis and the like of micropterus salmoides, and can effectively improve the breeding efficiency and accuracy of improved varieties of micropterus salmoides; and a new variety of largemouth micropterus salmoides which is more suitable for market requirements and is more competitive can be cultivated.

System and methods for alerting a healthcare provider to prescribed treatments having reduced or no effectiveness due to genetic composition is provided. A database containing treatments known to have reduced or no efficacy in persons having particular genetic markers is queried to determine whether any treatments prescribed by, or likely to be prescribed by, a healthcare provider to the patient are known to have reduced or no efficacy in persons having the same certain genetic markers as the patient. An alert indicating such information is displayed at a healthcare provider system.

The invention discloses a tumor immunotherapy curative effect prediction method and system based on multi-modal data, and the method comprises the steps: firstly, obtaining the multi-source tumor data of a patient, including pathological image data, medical image data, genome and molecular data, and clinical and demographic indexes; secondly, processing the multi-source tumor data to form a unified data set; thirdly, aiming at different modal data, adopting a corresponding feature extraction sub-network to extract each modal depth feature; then, a cross-modal attention mechanism is adopted to realize feature dynamic weighting and deep fusion, and unified multi-modal fusion representation is obtained; then, constructing a prediction model, and outputting an immunotherapy benefited population classification identification result, RECIST curative effect multi-classification prediction and survival prediction; and finally, generating a visual result and a feature contribution degree ranking of a prediction basis, and forming a clinical auxiliary decision report. According to the method, the prediction accuracy and stability can be remarkably improved, and meanwhile, the method has result interpretability and clinical application value.

The invention discloses L-arabinose isomerase, engineering bacteria and application, the amino acid sequence of the L-arabinose isomerase is shown as SEQ ID NO: 3, and the gene sequence for coding the L-arabinose isomerase is shown as SEQ ID NO: 2. On the basis of a genome of a Peribacillussp.S4 strain, a gene for coding the L-arabinose isomerase is excavated, and a stable prokaryotic expression system is constructed by performing codon optimization on the gene, so that the large-scale controllable production of the L-arabinose isomerase is realized, the yield of the enzyme is remarkably increased, the production cost of the enzyme is reduced, and the method is suitable for industrial production. A stable and economical enzyme source is provided for the production of D-tagatose; the L-arabinose isomerase expressed by the constructed engineering bacteria can significantly improve the yield of D-tagatose, and industrialization of D-tagatose is facilitated.

The invention provides a genetically engineered bacterium for producing O-succinyl-L-homoserine as well as a construction method and application of the genetically engineered bacterium. In a chassis bacterium genome, the expression of a 2-ketoglutaric acid decarboxylase encoding gene sucA is enhanced, and the expression of a succinyl-coenzyme A synthetase encoding gene sucD is weakened, so that the supply of succinyl-coenzyme A is increased; the method comprises the following steps: increasing the NADPH (Nicotinamide Adenine Dinucleotide Phosphate) reducing capacity and ATP (Adenosine Triphosphate) energy supply of a chassis bacterium, increasing DNA (Deoxyribose Nucleic Acid) in combination with a transcription dual regulatory factor ompR to improve the stress resistance of escherichia coli under high osmotic pressure, and introducing an overexpression plasmid containing a homoserine transsuccinylase coding gene metA to construct the genetically engineered bacterium for producing O-succinyl-L-homoserine. The engineering strain obtained through a systematic metabolic engineering modification strategy can realize effective accumulation of OSH, the shake flask yield of OSH reaches 19.8 g / L, the fed-batch fermentation yield of a 5L fermentation tank reaches 110.5 g / L, the sugar-acid conversion rate reaches 52.6%, and a foundation is laid for subsequent construction of high-yield OSH engineering bacteria.

The use of an SNP site combination of Litopenaeus vannamei in trait evaluation of mixed-family culture, a probe and a kit. The SNP site combination of Litopenaeus vannamei comprises 1125 SNP sites, wherein the physical positions are determined on the basis of alignment with a reference genome sequence of Litopenaeus vannamei. Also disclosed are a molecular probe for capturing the SNP site combination and a kit comprising the molecular probe. By means of using the SNP site combination for paternity identification, the present invention can achieve the mixed culture of individuals of different families in the early stage, so that the common environmental effect caused by separate family culture in the early stage is effectively reduced, and the accuracy of a trait evaluation result of mixed culture is improved; moreover, the genetic relationship between individuals can be accurately calculated. Compared with physical marks, the present invention avoids the phenomena of falling and dislocation of marks on individuals and human identification errors, thus obtaining accurate pedigrees.

The invention discloses a rice drought resistance phenotype detection and genetic analysis method based on a phenotypic robot, which is characterized in that rice hyperspectral phenotypic character data is acquired based on the phenotypic robot, and the relative water content RWC of rice is predicted. Through high-frequency data acquisition, RWC (t) based on a time sequence is obtained, RWC (t) curve change characteristic indexes are calculated, the dynamic change process of a rice experiment material in the whole drought experiment period is quantified, the drought resistance index DTI of the rice experiment material is obtained, and the drought resistance of the rice variety is comprehensively evaluated. DTI as a user-defined phenotypic character can be used for whole genome association analysis (GWAS), and a key gene for controlling the drought resistance of rice is excavated. According to the invention, the problems of low efficiency and low flux of traditional rice phenotype detection are solved, phenotype-gene mining based on the mobile robot is realized, and a new way is expanded for improvement of rice genetic breeding.

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 belongs to the technical field of pig molecular marker-assisted selection, and particularly relates to application of an SNP molecular marker related to the character of the number of live piglets born by pigs. The SNP molecular marker is a basic group of a 32663785th site of a ninth chromosome in a pig genome Sscrofa11.1. 109, the SNP site of the molecular marker has C / T polymorphism, and T is a favorable allelic variation of the character of the number of live piglets born by a pig. The dominant alleles of the SNP are preferably selected, the frequency of the dominant alleles can be increased generation by generation, the number of live piglets of pigs is increased, and the genetic improvement progress of the pigs is accelerated, so that the breeding and production benefits of the pigs are effectively improved.

A genome characterisation system for providing a genome characteristic prediction of a genome of origin associated with an input genomic sequence, the genome characterisation system comprising: an input preparation layer arranged to encode the input genomic sequence in a form suitable for input to a convolutional neural network; a multi-path residual block comprising a plurality of parallel residual routes, each residual route being adapted to receive input data from the input preparation layer and generate residual data corresponding to features of differing length; a self-attention layer arranged to receive residual data from each of the residual routes, generate a set of attention weights based on the residual data and a set of weights, and apply the set of attention weights to the residual data to generate an output tensor comprising data indicative of a relative importance of one or more portions of the input genomic sequence; and an output layer arranged to receive the output tensor from the self-attention layer; and output a likelihood vector indicative of characteristics of the genome of origin.

The invention discloses a corn genetic performance prediction method fusing multiple environmental factors. The corn genetic performance prediction method comprises the following steps: acquiring a parent genotype data matrix, a hybrid phenotype data vector and a multi-environmental time sequence climate data tensor; a climate hysteresis effect matrix is constructed, and hysteresis influence degrees of different climate factors on corn growth and development are quantified; constructing an environment time-space relation matrix and an enhanced genome relation matrix considering non-equal contributions of sections; constructing a linear hybrid prediction model fusing the space-time environment information; estimating a variance component through a constraint maximum likelihood method, and solving model parameters based on a Henderson hybrid model equation; and predicting the phenotypic character of the to-be-predicted corn hybrid in the target environment by using the solving parameters. According to the method, the genotype data and the multi-environment time sequence climate data are fully utilized, the genotype effect, the environment space-time effect and the interaction effect of the genotype effect and the environment space-time effect are effectively integrated, and the accuracy of corn hybrid phenotype prediction is remarkably improved.

The invention discloses a KASP marker for auxiliary screening of cold-resistant wheat germplasm and application of the KASP marker, and relates to the technical field of biology, in particular to a method for screening or auxiliary screening of wheat cold-resistant germplasm, which comprises the following steps: detecting whether the genotype of wheat to be detected is genotype qFR-7A. 1a or genotype qFR-7A. 1b; the cold resistance of the wheat with the genotype qFR-7A. 1a is higher than that of the wheat with the genotype qFR-7A. 1b, or the cold resistance of the wheat with the genotype qFR-7A. 1a is higher than that of the wheat with the genotype The wheat of which the genotype is qFR-7A. 1a is wheat of which the genotype is GG homozygous based on a G101A SNP (Single Nucleotide Polymorphism) site; the wheat of which the genotype is qFR-7A. 1b is wheat of which the genotype is AA homozygous based on a G101A SNP (Single Nucleotide Polymorphism) site; the G101A SNP site is the 101 nucleotide from the 5'terminal of SEQ ID NO: 1 in a wheat genome. The molecular marker has important theoretical significance and economic value for molecular marker-assisted selection of wheat germplasm or breeding offspring materials with relatively high cold resistance.

The invention provides a structure, a sequence and a construction method of a plant virus gene editing vector and application of the plant virus gene editing vector in plant gene editing. The method is characterized in that a TRV2 genome of a tobacco embrittlement virus (TRV) is used for carrying and expressing a small Cas gene AsCas12f and gRNA of the small Cas gene AsCas12f. Preferably, the AsCas12f and the gRNA of the AsCas12f are subjected to tandem expression by utilizing the TRV2 to form an expression cassette structure of the AsCas12f-tRNA-gRNA, the expression cassette substitutes a part of 2b gene sequence of the TRV2 on a TRV2 genome to form a plant gene editing vector pTRV2-Cas12f-gRNA based on the TRV virus, and long-time stable expression and gene editing can be performed after wild type nicotiana benthamiana is inoculated. The invention also provides a method for carrying out gene editing in a wild type plant by utilizing the plant virus.

The invention belongs to the technical field of genes, and discloses a method for efficiently expressing a foreign protein based on an NC048604-1 site in a CHO cell genome. A site for stably expressing protein in the CHO cell genome is located in the 94142000 to 94148000 basic group range of the CHO cell genome NC048604-1, and the nucleotide sequence of the site is as shown in SEQ ID NO: 1. According to the invention, different protein genes are introduced at fixed positions in a CHO cell genome, and stable expression is carried out.

The invention discloses an AI-based gene data analysis system. The system comprises a plurality of omics data matrixes; local association pattern mining is performed on the multi-omics data matrix through a 1D-CNN one-dimensional convolutional neural network, a topological structure of a gene network is identified through continuous coherence analysis, dynamic weights are allocated to sequence features and a topological feature matrix by using a dynamic attention mechanism, and weighted multi-scale feature vectors are output; establishing a multi-modal fusion model based on a Transform architecture to fuse the multi-scale feature vectors, performing fine adjustment on the adaptive disease data set by using the general genome feature of a pre-training model, and outputting a fused feature vector; and inputting the fusion feature vector into an MLP multilayer perceptron for disease risk prediction, generating a disease risk prediction index in combination with an SHAP algorithm, and generating an auxiliary decision scheme according to the prediction index. And the accuracy and generalization ability of disease risk classification are effectively improved.

Methods, systems, and software for estimating circulating tumor fraction are provided. A first plurality of nucleic acid sequences for a plurality of loci in genomic DNA from a solid tumor sample is obtained. A second plurality of nucleic acid sequences for a plurality of cell-free DNA fragments obtained from a liquid biopsy sample from the same subject is obtained. One or more somatic mutations is identified in the first plurality of nucleic acid sequences. A variant allele frequency (VAF) is determined for each somatic mutation based on a frequency of the respective somatic mutation in the liquid biopsy sample and a frequency of the corresponding wild type allele in the liquid biopsy sample, thereby determining a set of VAFs. An estimate of the circulating tumor fraction for the test subject is determined based on the set of VAFs for the one or more somatic mutations.

The invention discloses a flora regulation and control method and system for soil micro-ecology, and belongs to the technical field of microbial flora regulation and control, and the method comprises the steps: continuously collecting real-time environment data based on a target soil region, combining future climate prediction data, and generating a predicted scene sequence through Monte Carlo simulation; constructing a microbial community composition table, screening core strains, and performing metagenome sequencing; taking the core strain as a game participant, constructing a participant strategy set, calculating an income matrix library, setting an environment correction coefficient for each scene, carrying out scene-based game solving, and generating a balanced summary table; a regulation response prediction model is constructed, multiple optimization objectives are set, robustness constraints and expert rules are introduced, candidate regulation schemes are generated, optimal scheme solving is carried out, it is ensured that regulation measures can achieve an expected effect by guiding inter-species competition, and original flora balance is prevented from being damaged.

The invention discloses a primer combination for identifying six genital tract pathogens and detecting drug resistance genes, a kit and application, the primer combination comprises a primer combination for identifying chlamydia trachomatis, mycoplasma genitalium, ureaplasma urealyticum, mycoplasma hominis, neisseria gonorrhoeae and trichomonas vaginalis and detecting the drug resistance genes of the six genital tract pathogens, and nucleotide sequences are shown as SEQ ID NO.1-SEQ ID NO.50. Microorganisms and related drug-resistant genes in a detection range are identified by utilizing a multiple PCR targeted three-generation sequencing method, the specificity is good, the sensitivity is high, the detection technology has important clinical significance when being applied to identification of genital tract infection pathogens, and compared with a traditional detection method, the detection flux, the coverage range and the sensitivity are higher, and detection is stable; compared with pathogenic microorganism metagenome (mNGS) detection, the method has the advantages that the detection cost is lower, and the detection sensitivity on drug-resistant genes and drug-resistant gene mutation is higher.

The invention discloses a peanut quality character selective breeding method based on whole genome SNP and application, and relates to the technical field of crop breeding, the method comprises the specific steps of data acquisition, SNP optimization and marker screening, model construction and new strain breeding; by integrating whole genome re-sequencing, SNP optimization marker screening and mixed deep learning model construction, peanut quality character prediction and breeding value evaluation are achieved, through whole genome re-sequencing and quality control processes, an SNP variation map is obtained, ten key quality characters including protein, oil content, oleic acid and the like are covered, and the breeding value of peanuts is evaluated. According to the method, comprehensive genetic information is provided for subsequent analysis, a feature marker set is formed by screening out sites in the SNP optimization and marker screening link, interference of low-quality sites is avoided, a whole genome selection model is obtained by adjusting and training a mixed deep learning model and optimizing hyper-parameters through ten-fold cross validation, the breeding period is shortened, and the breeding efficiency is improved. And the prediction error rate is reduced.

The invention belongs to the technical field of plant fungus molecular biology detection, and discloses an LAMP primer group, a kit and a detection method for detecting oat smut pathogenic bacteria. A group of LAMP (loop-mediated isothermal amplification) specific primers are designed according to a specific sequence on a whole genome of the oat smut pathogenic bacteria Ustilago hordei, results are judged through a real-time fluorescence quantification method, an agarose gel electrophoresis method and an SYBR Green I fluorescent dye developing method, and the oat smut pathogenic bacteria carried by oat seeds are detected. The LAMP detection method for the oat smut pathogenic bacteria, established by the invention, is strong in specificity, high in sensitivity, high in speed and low in cost, provides a new technical means for detection of the oat smut pathogenic bacteria carried by the oat seeds, and has relatively high practical application value.