6817 results about "Genome" patented technology

A federated distributed computational system enables secure biological data analysis and genomic medicine with enhanced oncological therapy capabilities. The system implements patient-specific tumor-on-a-chip analysis through microfluidic control systems and cellular heterogeneity preservation, while integrating fluorescence-enhanced diagnostics using CRISPR-LNP targeting and robotic surgical navigation. The architecture coordinates spatiotemporal analysis of gene therapy delivery through molecular imaging and immune response tracking, and implements bridge RNA integration with multi-target synchronization. Treatment selection is optimized through multi-criteria scoring and patient-specific simulation modeling. Each federated node contains a local processing unit for biological data analysis, privacy preservation protocols, and a hierarchical knowledge graph structure. The system implements cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration, enabling research institutions to collaborate on complex, large-scale biological analyses while maintaining strict data privacy controls.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

Provided herein are methods of identifying genetic variants in biological samples. In particular, the present disclosure uses spatial transcriptomic templated ligation methods and compositions to identify the presence or absence, and the location of genetic variants in the transcriptome or genome of a biological sample.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

A federated distributed computational system enables secure, multi-institutional biological data analysis and genomic medicine through interconnected, decentralized nodes in a federated distributed graph architecture. A federation manager coordinates computational resource allocation, control and data flows, establishes privacy and security boundaries, implements multi-scale spatiotemporal analysis and simulation modeling, models cross-species or intrapopulation elements, and maintains cross-institutional knowledge relationships. Each node includes a local processing unit for biological data analysis, including multiomics and gene editing, privacy-preserving protocols for secure multi-party computation, a hierarchical knowledge graph for managing multi-domain biological relationships across spatial and temporal scales, and encrypted network connections. The system implements cross-species genetic analysis via phylogenetic integration, environmental response modeling through spatiotemporal tracking, and multi-scale tensor-based data integration with adaptive dimensionality control. This architecture enables research institutions to collaborate on complex biological analyses and genomic medicine applications while maintaining strict data privacy and security controls.

A federated distributed computational system enables secure biological data analysis and genomic medicine through hybrid simulation capabilities. The system implements a hybrid simulation orchestrator that coordinates classical numerical simulations with machine learning models for biological system analysis, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for biological data analysis and privacy preservation protocols. The system implements cellular machinery assembly analysis, real-time patient data integration, and multi-modal image integration with spatiotemporal health data annotation. Through a distributed graph architecture, the system enables cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration with adaptive dimensionality control. The system implements real-time therapeutic response prediction through multi-modal data analysis, enabling research institutions to collaborate on complex biological analyses while maintaining strict data privacy controls.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

The invention relates to the technical field of database construction, in particular to a construction method and system for a reproductive medicine database. The method comprises the following steps: acquiring a biological tissue sample of a patient; acquiring reproductive endocrine hormone data, embryo morphological parameter data, immune cell function data and genome variation data from the biological tissue sample of the patient; performing time sequence analysis processing on the hormone fluctuation mode according to the reproductive endocrine hormone data to obtain endocrine dynamic characteristic data; performing image recognition processing based on coherent superposition characteristics of light on the embryo morphological parameter data, and performing embryo development potential evaluation to obtain embryo development potential data; and performing hierarchical clustering processing on the individual heterogeneity of the patient according to the immune cell function data and the genome variation data to obtain immune-genetic typing data of the patient. By means of the quantum dot sensing technology and the multi-channel micro-fluidic chip, standardization of data acquisition is achieved, and the heterogeneity problem of a data source is solved.

The invention belongs to the technical field of biology, and relates to an escherichia coli engineering strain for producing L-isoleucine through a methyl malic acid way as well as a construction method and application of the escherichia coli engineering strain. According to the invention, Escherichia coli BW25113 is used as a chassis strain, and a methyl malic acid synthase high-activity mutant gene cimA3.7, an isopropyl malic acid isomerase gene GsleuCD, a 3-isopropyl malic acid dehydrogenase gene AfleuB and a leucine dehydrogenase gene Lsleudh are over-expressed; a methyl malic acid absorption protein gene is over-expressed, and a branched chain amino acid transport system is modified to improve the exosome of the L-isoleucine; all methyl malic acid pathway related genes are integrated to a genome of a chassis strain, and a plasmid-free L-isoleucine production strain is constructed; the copy number of a key gene on a genome is optimized, and the yield of the engineering strain L-isoleucine is increased by introducing a non-oxidative glycolysis approach. The yield of the L-isoleucine after the engineering strain is fermented for 34 hours in a fermentation tank is 56.6 g / L.

The invention relates to the field of microbial communities, and discloses a bioinformatics-based microbial community dynamic monitoring method, which comprises the following steps: acquiring high-frequency acquisition data based on a trace sample, constructing a microbial data stream for time sequence analysis, and carrying out rapid metagenome marker amplification on each sampling unit in the data stream, obtaining a preliminary feature matrix; based on the co-occurrence frequency of the microbial functional genes in the preliminary feature matrix, constructing a multi-dimensional feature mapping graph; performing real-time mode recognition on the flora abundance change trend based on the dynamic fluctuation region; aiming at the key dynamic signal segment, adopting a distributed clustering method based on variation information entropy regulation and control to reconstruct the evolution trajectory of the flora, and generating a flora time sequence behavior vector set; and based on the flora time sequence behavior vector set, performing dynamic alignment with a pre-constructed reference model by using a multi-scale trend matching algorithm. The method has the advantages of high timeliness and automatic processing capability.

The invention discloses an interpretable machine learning genome prediction method and device, belongs to the technical field of combination of biological breeding, biological information and machine learning, and utilizes an advanced machine learning algorithm to perform parameter optimization in combination with biological prior information. Through processing of multi-source data (genome, transcriptome and epigenetic data), dynamic feature engineering (PCA and PHATE dimensionality reduction) and organic combination of various machine learning models, and an automatic parameter adjustment framework based on a grid search and sparrow search algorithm, genome prediction precision and calculation efficiency are significantly improved; meanwhile, the interpretability of the model is realized based on the SHAP value, the SNP site contribution is quantified, a reference is provided for precise breeding, and the method is suitable for animal and plant molecular breeding and medical genetic analysis, and can accelerate genetic analysis of high-value characters, assist precise breeding decision and disease risk prediction, and promote leap-forward development from experience breeding to intelligent breeding.

The invention discloses a sugarcane germplasm resource evaluation and breeding method for smart agriculture. The sugarcane germplasm resource evaluation and breeding method comprises the following steps: step 1, collecting materials with wide genetic diversity; establishing an intelligent incubator and a greenhouse, and monitoring environmental parameters by using an Internet of Things sensor; 2, performing data acquisition on the related germplasm resources by using an unmanned aerial vehicle, a robot and a near infrared spectrum technology, and constructing a phenotype database for data management; meanwhile, genotype identification is carried out by combining molecular marker-assisted selection and genome selection technologies, molecular markers of key genes are mined, and the genetic value of related germplasm is evaluated; step 3, constructing a hybrid combination prediction model by using an AI algorithm, optimizing parent matching of the related germplasm and the cultivated sugarcane, monitoring and collecting the filial generation at the same time, and analyzing and screening in combination with smart agriculture; 4, demonstration planting is conducted on the bred excellent sugarcane strain, and application of the excellent strain is improved through government-enterprise-scientific research institution collaborative popularization and in combination with farmer technical training.

The invention discloses a livestock epidemic disease early warning method and system based on big data analysis, and the method comprises the steps: generating a preliminary epidemic situation diffusion path through employing the farm distribution and traffic network data of a geographic information system in combination with a space-time propagation model, and carrying out the dynamic adjustment according to the real-time updated data; predicting a high-risk area by adopting a multi-source data fusion early warning model; the strain mutation risk is judged by analyzing the relevance between pathogen genomes and environmental parameters; deploying a deep learning model at an edge computing node, analyzing animal husbandry behaviors and voiceprint data in real time, and evaluating the animal husbandry health state; and integrating mutation risk analysis and animal husbandry health assessment results to generate a comprehensive epidemic situation early warning report. Through multi-dimensional data analysis and edge intelligent calculation, accurate early warning of animal epidemic situations is realized, and a scientific basis is provided for epidemic situation prevention and control.

The invention discloses a molecular marker for auxiliary screening of anti-freezing wheat germplasm and application of the molecular marker, and relates to the technical field of biology, in particular to a method for screening or auxiliary screening of wheat with different freezing resistance, which comprises the following steps: detecting whether the genotype of wheat to be detected is qFDG-7A. 3a or qFDG-7A. 3b, and the freezing resistance gt of the wheat with the genotype qFDG-7A. 3a; the freezing resistance of the wheat with the genotype qFDG-7A. 3b; the wheat of which the genotype is qFDG-7A. 3a is wheat of which the genotype is AA homozygous based on an A129C SNP (Single Nucleotide Polymorphism) site; the wheat of which the genotype is qFDG-7A. 3b is wheat of which the genotype is CC homozygous based on an A129C SNP (Single Nucleotide Polymorphism) site; the A129C SNP site is the 129th nucleotide from the 5'tail end 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 progeny materials with high anti-freezing capacity.

The invention provides a clinical test result prediction model driven by multi-modal data, which relates to the technical field of digital data construction and comprises a data acquisition and preprocessing module, a feature extraction and fusion module, a self-adaptive prediction model, a feedback and updating module and a visualization module. By fusing multi-modal information such as images, genomes, laboratory data and text records, the scheme can more comprehensively obtain multi-dimensional health data of the patient. The feature dynamic weight distribution module dynamically adjusts the weights of different modal data based on global and local attention mechanisms, and ensures the prominent contribution of key features in different prediction scenes, thereby significantly improving the prediction precision and stability of the model.

The invention relates to a saccharomyces cerevisiae strain for efficiently synthesizing cordycepin as well as a construction method and application of the saccharomyces cerevisiae strain, and belongs to the technical field of microbial genetic engineering. The construction method provided by the invention comprises the following steps: carrying out multi-copy genome integrated expression on heterologous codon optimized 2 '-carbonyl-3'-deoxyadenosine reductase genes and 3 '-adenosine monophosphate phosphohydrolase genes, so as to increase the dosage of key enzymes; and supplementing the defective gene of the engineering strain to obtain the saccharomyces cerevisiae strain B5U3 with high yield of cordycepin. According to the obtained saccharomyces cerevisiae strain for efficiently synthesizing the cordycepin, the cordycepin yield reaches 2.92 g / L after shake flask fermentation, the cordycepin yield reaches 7.5 g / L after fermentation in a fermentation tank, and a foundation is laid for safer and more reliable industrial production of the cordycepin.

The present invention relates to the construction of a high-yield indigo genetic engineering strain and a fermentation method. The present invention uses Escherichia coli as a starting strain, knocks out at least one of the yddG gene, trpR gene, tyrA gene or pheA gene in the host cell; integrates the tryptophanase gene tnaA and / or the flavin monooxygenase gene MaFMO on the genome; integrates one or more genes related to biofilm modification on the genome, and obtains the optimal engineering strain by comparing the fermentation yield; then transfers a plasmid into the strain to further strengthen the tryptophanase gene tnaA and the flavin monooxygenase gene MaFMO; finally, the yield is significantly increased by supplementing carbon sources and substrates and adding surfactants. The present invention provides an indigo-producing genetic engineering strain and a fermentation method with good stability and high synthesis efficiency, providing a reference for the subsequent development of more advantageous engineering strains.

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 discloses a primer combination for detecting monkey pox viruses and identifying monkey pox viruses Ia, Ib and II, and belongs to the technical field of molecular biology, the nucleotide sequences of specific primers and probes are shown as SEQ ID NO.1-SEQ ID NO.12, and the primer combination aims at solving the problem that in the prior art, new evolutionary branch Ib types of monkey pox viruses cannot be accurately typed, and the detection sensitivity is high. According to the present invention, the defects that the monkey pox virus and the orthopox virus have the cross reaction are overcome, the genome difference of different evolutionary branches is analyzed through the bioinformatics system, the primer probe composition capable of simultaneously detecting the monkey pox virus and carrying out accurate typing is analyzed and screened, and the primer combination can detect 200 copies / mL of the monkey pox virus with high specificity and high sensitivity. Meanwhile, detection of the monkey pox virus and identification of the types Ia, Ib and II of the monkey pox virus are realized in a reaction system, so that different monkey pox branches can be distinguished, and treatment and prevention can be performed in a more targeted manner.

The invention provides a risk prediction method and system for cardiovascular and metabolic diseases. The method comprises the following steps: collecting continuous cardiovascular-metabolism time sequence data, and extracting phase delay parameters to construct a lipid transport rhythm out-of-synchronization characteristic spectrum; quantifying the topological connection strength of the gene cluster based on the three-dimensional genome interaction strength matrix, and generating a genetic prediction model; a vascular endothelial metabolism buffer attenuation trajectory is calculated through simulation, and a critical environment exposure parameter is determined by matching a genetic instability threshold value; and fusing multi-source data to construct a dynamic toughness model, calculating a phase space shrinkage rate of a vascular metabolism steady-state boundary, and triggering graded early warning. According to the technical scheme provided by the invention, ultra-early warning of cardiovascular metabolism risks is realized, and the individual intervention target spot recognition precision is improved.

The embodiment of the invention discloses a KASP molecular marker, a primer pair and a kit for identifying the dwarf character of muskmelon and application of the KASP molecular marker, relates to the technical field of molecular markers, and aims to promote gene positioning and molecular-assisted breeding processes by utilizing molecular marker-assisted selective breeding on the dwarf character of muskmelon. The method for identifying the dwarf character of the muskmelon comprises the following steps: extracting genome DNA of a target muskmelon, taking the genome DNA of the target muskmelon as a template for PCR amplification, and performing fluorescence detection based on a primer of a KASP marker K1069930 to obtain a gene type of the target muskmelon, on the basis of the detected gene type, the character of the target muskmelon is judged; the KASP marker K1069930 is designed according to an SNP (Single Nucleotide Polymorphism) site at Chr07: 1069930, and the nucleotide sequence of the SNP site is shown as SEQ ID NO. 1. The invention also discloses a kit for detecting the KASP marker K1069930 and a kit for detecting the KASP marker K1069930. The identification method provided by the invention can be more efficiently applied to breeding work of dwarf muskmelon germplasm.

The invention discloses a sheep whole genome SNP molecular marker, which comprises 50000 SNP molecular markers, the SNP molecular marker is composed of 5235 functional SNP molecular markers and 44765 SNP molecular markers, the functional SNP molecular markers mainly select variation sites related to economic traits (such as growth, slaughtering, meat quality, breeding, lamb and the like) of sheep, and the variation sites are selected from the variation sites. And the background SNP molecular marker is used for improving the typing precision and polymorphism coverage of the chip, so that the applicability of the chip in a large-scale group is ensured.

A resistance gene TaCAT to FCR of wheat and an application thereof are provided, which relates to the field of biological genetic engineering technologies. The nucleotide sequence of a genome where the TaCAT gene is located, the nucleotide sequence of a cDNA, the nucleotide sequence of a CDS and a coded protein sequence are respectively as shown in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3 and SEQ ID NO: 4. An InDel marker is developed for identifying different allelotypes of the TaCAT gene. An application of the TaCAT gene for preparation of transgenic plant cells and plant breeding is provided. The molecular genetic basis of the resistance to FCR is disclosed, an important role is played in improving the resistance to FCR by utilizing a genetic engineering technology, and a new way is provided for breeding a new wheat variety with disease-resistance and safety.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker combination for constructing an oat DNA (Deoxyribose Nucleic Acid) fingerprint spectrum and application, the SNP molecular marker combination is developed and obtained based on an SLAFseq technology, and has the characteristics of uniformly covering an oat genome, being high in polymorphic information content and being suitable for typing. Compared with other traditional molecular marker technologies, the SNP marker provided by the invention has higher stability, is not easily influenced by experimental conditions and environmental factors, and can be widely applied to oat germplasm resource identification, genetic diversity analysis, DNA fingerprint construction and molecular marker-assisted breeding. The DNA fingerprint spectrum constructed on the basis of the SNP molecular marker can more comprehensively reflect genetic information of a biological individual or population, and is of great significance to research of genetic diversity, evolutionary relationship and the like of species. Therefore, the method can provide technical reference for popularization of oat varieties, property right confirmation and protection, purity identification of oat seed production and the like.

The present disclosure provides compositions, methods, systems, and devices for polynucleotide processing and analyte characterization. Such polynucleotide processing may be useful for a variety of applications, including analyte characterization by polynucleotide sequencing. The compositions, methods, systems, and devices disclosed herein generally describe barcoded oligonucleotides, which can be bound to a bead, such as a gel bead, useful for characterizing one or more analytes including, for example, protein (e.g., cell surface or intracellular proteins), genomic DNA, and RNA (e.g., mRNA or CRISPR guide RNAs). Also described herein, are barcoded labelling agents and oligonucleotide molecules useful for “tagging” analytes for characterization.

Disclosed are a genome-wide low-density SNP chip for milk goats and a use thereof. The provided SNP chip is applicable to genetic improvement of economic traits of European milk goat varieties and Chinese native milk goat varieties, can also be applied to a plurality of fields of milk goat genome-wide association study, genome-wide selection breeding, population genetics analysis, trait-related candidate genes, QTL analysis and locating, and the like, and has high value in production application and scientific research.

The invention discloses an HNRNPA2B1 gene-based bovine sperm malformation rate related SNP molecular marker and application thereof, and belongs to the technical field of genetic molecular biology, the number of the SNP molecular markers is two, SNP1 is at the position of a bovine genome chr4: 69733358, the polymorphism is C or A, SNP2 is at the position of a bovine genome chr4: 69733387, and the polymorphism is T or G. According to the two SNP loci provided by the invention, the dominant genotypes of g.-1713A > C and g.-1684G > T are AA and GG respectively, and the sperm collection quantity and the sperm malformation rate of the two SNP loci have better performance. By detecting the polymorphism of the two SNP loci, the motility evaluation of the bull sperms can be realized, the breeding is assisted, a reliable support is provided for breeding a high-quality next generation, and the method has the advantages of high reliability, high efficiency, low cost and the like.

The invention provides a method for genetically modifying bordetella pertussis and application of the method. The method comprises the following steps: knocking down or knocking out a first nutrition screening gene of bordetella pertussis to generate a first auxotrophic cell; replacing the first genetic element with a second nutrition screening gene through recombination treatment to obtain a second auxotroph cell; replacing the second nutritional screening gene with the genetically modified second genetic element through recombination treatment to obtain a third nutritional deficient cell; and restoring the first nutritional screening gene to the genome of the third nutritional deficient cell through recombination treatment. In the modification process, use of antibiotics is not involved, no redundant fragments are introduced except for target modification sites, and the method has the advantages that the genetic background purity is high, and no biological safety risk exists in the modification process.

The invention discloses a specific molecular marker, primers, a method and application for genetic sex identification of siniperca chuatsi, the specific molecular marker has two sequences in male fish and has one sequence in female fish, the primers comprise an upstream primer F and a downstream primer R. The primers are adopted to carry out PCR amplification on genome DNA of the siniperca chuatsi to be detected, and the specific molecular marker is obtained. And identifying the genetic sex of the siniperca chuatsi according to an agarose gel electrophoresis detection result. The invention further discloses application of a reagent, a primer, a kit or a method for detecting the specific molecular marker in genetic sex identification of siniperca chuatsi, artificial breeding of the siniperca chuatsi or all-female breeding of the siniperca chuatsi. The siniperca chuatsi genetic sex identification method has the advantages that sex-related male and female differential fragments are found through combined comparative analysis of male and female genomes, primers are designed for amplification verification, only a small amount of DNA of a to-be-detected sample genome is needed as a template, the genetic sex of the siniperca chuatsi can be accurately, simply, conveniently, quickly and stably identified only through PCR and agarose gel electrophoresis, and the method is not limited by the development stage of the siniperca chuatsi.