3820 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 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.

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 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.

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 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.

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.

The invention provides a nucleotide mutation site prediction model construction and disease-related point mutation identification method. Specifically, the invention provides a deep learning model-fused nucleotide mutation site prediction model construction method and a disease-related point mutation identification method. According to the method, DNA point mutation and RNA point mutation can be recognized from transcriptome sequencing data in a high-sensitivity and high-specificity mode, and basic data is provided for explaining mutation generation mechanisms and functions on the whole transcriptome and genome level.

The invention belongs to the technical field of molecular biology and plant molecular breeding, and particularly relates to a mustard core SNP molecular marker set and a screening method and application thereof. The invention provides a core SNP marker set (33) which is subjected to whole genome re-sequencing screening and experimental verification and is suitable for mustard germplasm resource identification and genetic analysis for the first time. The marker set is high in polymorphism and good in stability, covers the whole genome and can effectively distinguish different leaf mustard germplasms. By utilizing the core marker set and the matched KASP primer, the genetic typing of the leaf mustard germplasm resources can be quickly and accurately performed with high throughput, and the defects that the traditional morphological identification is time-consuming, labor-consuming and poor in accuracy are overcome. The marker set can be used for analyzing the genetic diversity, the population structure and the phylogenetic relationship of the leaf mustard germplasm resources, and a molecular basis is provided for collection, preservation and evaluation of the germplasm resources and breeding parent matching.

The invention belongs to the technical field of gene detection and gene molecular breeding, and particularly relates to a meat duck whole genome molecular probe combination based on molecular phenotype screening, a 50K gene chip and application thereof. The molecular probe combination and the gene chip of the marker site combination for meat duck whole genome breeding simultaneously cover 7 representative meat duck varieties and 71 economic characters, have richer polymorphism and higher pertinence in meat duck groups, and are lower in cost and higher in speed compared with high-throughput sequencing detection; the breeding chip is designed according to the growth, feed efficiency, slaughtering, breeding, egg quality and various molecular phenotypes of the meat ducks, and compared with a high-throughput sequencing technology, the breeding chip is higher in seed selection accuracy, has higher breeding value, can be widely applied to breeding genotype detection of the meat ducks, and can be used for detecting the breeding genotypes of the meat ducks. And the method has creative significance in the aspect of meat duck genome selective breeding.

The invention discloses a bacterial selenoprotein online resource platform, an application method, a terminal and a medium, and relates to the technical field of biological medicine, the online resource platform is deployed on a server, the cloud server is a Ubuntu cloud server, and Nginx, Waitpress and Flask are configured; the server side is in butt joint with a background resource, and the background resource is in butt joint with the constructed bacterial selenoprotein database; the server is in butt joint with a user interface of the front end, the user interface designs a corresponding interface framework and an interaction function based on static resources hosted by Nginx, and the interaction function is used for realizing query, analysis and use of relevant information of the bacterial selenoprotein. According to the method, a convenient online access channel of an integrated database and a real-time data analysis tool are provided for users in related fields, and important support is provided for accurate annotation of selenoprotein genes in a bacterial genome plan.

The invention relates to the field of gene engineering. In particular, the present invention relates to cytosine deaminases and their use in base editing. More specifically, the invention relates to a method for screening and identifying a deaminase, a base editing system based on a newly identified cytosine deaminase, a method for editing a target sequence in a genome of an organism (such as a plant) by using the base editing system, and a method for screening and identifying the target sequence. As well as genetically modified organisms (e.g., plants) and progeny thereof produced by the method.

The invention provides application of a tobacco NtMYC1 gene in promoting growth and development of tobacco glandular hair, and belongs to the technical field of plant breeding. The tobacco MYC1 transcription factor is obtained by carrying out sequence characteristic analysis, conservative structural domain identification, protein physicochemical property analysis and phylogenetic analysis on a genome of tobacco. And an RNAi technology and an overexpression tobacco transgenic line verify that the tobacco MYC1 transcription factor and the coding gene thereof have the effect of regulating and controlling the growth and development of the tobacco glandular hair, and the growth and development of the tobacco glandular hair are promoted through forward regulation and control, so that the growth and development of the tobacco glandular hair are inhibited through silent expression. Therefore, the tobacco MYC1 transcription factor and the coding gene thereof provided by the invention provide a new means for tobacco breeding.

The invention belongs to the technical field of biology, and particularly relates to a synthetic probiotic phenotypic characteristic prediction method and system.The method comprises the steps that a genome is divided into gene units, K-mer sequences containing position weights and codon coding information are extracted from the gene units, and an initial characteristic vector is constructed for each strain; by calculating mutual information between each K-mer feature and a known phenotype, identifying which gene segments are most critical for predicting a target phenotype, and distributing significance weights for the gene segments; after the feature vectors of the known strains are optimized and weighted through the weights, a machine learning prediction model is trained; and when a new synthetic probiotic needs to be predicted, executing the same feature extraction and weighting process on the genome of the new synthetic probiotic, and inputting the obtained vector into the trained model to obtain a prediction result of the phenotypic features of the new synthetic probiotic.

An automated high throughput screening platform for identification of compounds and genomic constructs having mitochondrial function modulating activity and compounds so identified are provided. Use of such compounds for modulating mitochondrial function are also disclosed. A high-throughput screening method of determining genetic mechanisms of action for therapeutic or toxic agents in genetic or pharmacologic models of disease are also provided.

The invention relates to the technical field of biomedicine, in particular to a method for constructing a plasma ctDNA organ distribution characteristic spectrum of advanced colorectal cancer. The method comprises the following steps: collecting a peripheral blood sample at multiple time points, separating plasma by adopting a double-centrifugal method, and extracting circulating tumor DNA (Deoxyribose Nucleic Acid); carrying out whole exome sequencing based on ctDNA to obtain genome variation information and calculating variation allele frequency, and synchronously detecting the expression quantity of immune-related proteins by adopting an Olink proteomics technology; integrating the genome data, the protein expression data and the clinical pathological features, and constructing a multi-dimensional feature data matrix; and taking the organ metastasis condition confirmed by iconography as a supervision label, training a model by applying a machine learning algorithm, screening key prediction factors, constructing a quantitative prediction model, and finally generating a visual organ metastasis tendency prediction map. According to the method, early and accurate prediction of the advanced colorectal cancer organ metastasis tendency is realized through multi-omics data collaborative analysis and machine learning modeling.

The invention discloses a cell membrane protein replacement type oncolytic virus vector and application thereof. The cell membrane protein replacement type oncolytic virus vector is rhabdoviridae virus, and a nucleotide sequence for coding G protein in a genome of the rhabdoviridae virus is replaced by a nucleotide sequence for coding an antibody and a nucleotide sequence for coding a spike protein truncation of coronavirus. The invention also discloses a construction method of the cell membrane protein replacement type oncolytic virus vector for expressing the antibody, the non-replicated virus vector is used for expressing the antibody sequence for the first time, and meanwhile, the novel coronavirus cell membrane protein is embedded into the virus surface, so that the cell membrane protein replacement type oncolytic virus vector can be rapidly produced in a suspension cell in a large scale; through removal of virus cell membrane protein genes, the virus cell membrane protein genes cannot be continuously replicated in vivo, so that the safety of the virus cell membrane protein genes is ensured, the tumor immunosuppression condition is improved, and an organism can be stimulated to generate a neutralizing antibody for resisting new coronavirus while tumor cells are killed.