329 results about "Gene Variant" patented technology

Provided herein are methods, compositions, and kits to spatially detect genetic variants in a target nucleic acid via templated-ligation and reversible terminator nucleotides.

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.

Provided herein are methods, compositions, and kits to spatially detect genetic variants in a target nucleic acid via templated-ligation and reversible terminator nucleotides.

A system and method for processing genomic data using dynamic latent manifolds that transforms multi-modal genomic datasets into geometric representations within a curved manifold space. The system receives genomic datasets including DNA sequences, genetic variants, and expression data, then extracts biological features and assesses importance using trained neural networks. Manifold curvature values are computed based on biological significance, and genomic data is embedded as geometric structures where semantic relationships are represented through distance and curvature properties. The system generates compression pressure fields that influence processing decisions and computes optimal geodesic paths through the manifold to minimize cognitive action functionals. Adaptive compression rates are determined for different genomic regions based on geometric properties and biological importance. The manifold structure evolves through use, strengthening frequently accessed pathways while applying thermodynamic decay to unused concepts. The system supports hierarchical organization across biological scales, reversible navigation, and federated learning capabilities that enable privacy-preserving collaboration.

Systems and methods for predicting a medical trait in an individual are provided. The techniques include obtaining genomic data including information indicative of genetic variants present in a genome of the individual and calculating, using an at least one processor and a trained computational model, a trait score based on the information indicative of the genetic variants, wherein the trained computational model was obtained by training a first computational model using data describing phenotypes, genotypes, and / or phenotype-genotype relationships for a population including admixed individuals of multiple ancestries. The trait score may be used to alter a course of medical treatment of the individual and / or to implement a clinical trial.

This application is directed to multiomic and biomimetic digital twin techniques for identifying disease-specific genetic variants. A computer system obtains information of subject genetic variants that are identified from a plurality of biological samples of a plurality of patients who are diagnosed with a target disease. A subset of subject genetic variants are selected based on a plurality of subject phenotypes of the target disease. The subset of subject genetic variants are ranked based on the plurality of subject phenotypes to generate subject genetic variant information. The computer system further obtains subject medical information of the plurality of patients. The computer system applies a biomimetic information model to process the subject genetic variant information, the subject medical information, and the general genetic variant information of the target disease and identify a set of target genetic variants associated with the phenotype of the disease(s) satisfying a variant selection criterion.

The invention relates to the technical field of gene variation detection, in particular to a gene sequence variation detection method based on robust statistics and multi-strategy fusion, which comprises the following steps: comparing to generate a sorted BAM file; preprocessing a missing value and an N position in the data, replacing the missing value by adopting a 0 filling strategy, and removing the data at the N position; extracting an RD signal and an MQ signal as characteristic values; performing GC deviation correction on the extracted RD signal; performing smooth noise reduction processing on the RD signal and the MQ signal; a two-step progressive segmentation strategy is adopted, and continuous fragments with highly consistent RD values are identified; constructing two-dimensional profiles of the RD signal and the MQ signal, and performing standardization processing; carrying out serial repeated detection and calculating an abnormal score; setting a threshold value by using a box plot method, and judging an abnormal value; and refining a tandem repeated region. According to the method, the problem of tandem repeat variation detection under low-coverage sequencing data is effectively solved, and the detection accuracy and reliability are remarkably improved.

The invention relates to a method for carrying out pathogenic microorganism identification and gene variation state joint detection on a pulmonary alveolar lavage fluid sample based on high-throughput sequencing. The method comprises the following steps: extracting nucleic acid from the pulmonary alveolar lavage fluid sample; constructing a metagenome capture library, and constructing a lung cancer polygene library; carrying out final library pooling; performing high-throughput sequencing; and analyzing data. Compared with the prior art, the scheme provided by the invention is based on a technical path of'macro 'captured by metagenome and'target' of targeted high-throughput sequencing; after the constructed final library is subjected to high-throughput sequencing and data analysis, index output (pathogenic microorganism identification, host chromosome copy number variation, gene mutation, gene fusion, gene copy number variation and methylation state) of multiple biomarkers can be met in one-time detection.

The invention discloses a human body electrocardio R wave detection method, and relates to the technical field of electrocardio signal detection.The system comprises the following components of gene expression data and electrocardio signal collection, specifically, gene expression level information of an individual whole genome is obtained through a gene detection technology, meanwhile, electrocardio signals are collected through a multi-channel electrocardio sensor, and the gene expression data and the electrocardio signals are obtained; according to the method, by introducing the gene expression data, personalized electrocardiogram R wave detection can be carried out on an individual with the tendency of specific gene variation or family genetic cardiovascular diseases, the conventional characteristics of the electrocardiogram signals are considered, information of the gene level is combined, and the method has the advantages of being high in accuracy and high in accuracy. Therefore, R waves can be recognized more accurately, false detection and missing detection are reduced, and the method has important significance in improving the accuracy of cardiovascular disease diagnosis, finding cardiovascular abnormality in an early stage and formulating a personalized treatment scheme.

The invention relates to the technical field of precision medical treatment, in particular to an interpretation system and method for tumor precision medication and a storage medium, and the system comprises a data collection module which is used for collecting gene data, clinical data and drug response data of tumor patients from a plurality of data sources; the data standardization processing module is used for carrying out formatting and standardization processing on the data, so that the data formats are consistent, and effective processing and analysis can be carried out in subsequent modules; the gene data analysis module is used for performing variation analysis according to the gene data of the patient, identifying a gene mutation site and generating a drug sensitivity analysis result; and the drug screening module is used for screening drugs matched with the gene variation sites of the patient from a drug database according to the gene data analysis result, and providing drug dosage recommendation. By adopting the technical scheme of combining a quantum optimization technology and gene data analysis, the technical effect of remarkably improving the drug screening and dose recommendation precision is achieved.

The invention relates to a multiplex PCR (Polymerase Chain Reaction) primer probe combination, a kit and a detection method for human red blood cell RHCE genetic typing detection, and belongs to the field of biomedicine clinical molecular detection. The invention provides a multiplex PCR (Polymerase Chain Reaction) primer probe combination for human red blood cell RHCE genetic typing detection, and further provides a kit containing the multiplex PCR primer probe combination. The method has the technical advantages that the RHCE gene variation site specific primer and probe are designed through an improved ARMS technology and a homologous sequence specific base method, so that higher specificity and accuracy are realized; only four-hole reaction is needed, detection of RHC, RHc, RHE, RHe, CW- / CW +, CX- / CX +, V-VS- / V + VS + and V + / V-can be completed at a time, and higher flux and efficiency are achieved; according to the method, multiple fluorescent PCR is combined with a Taqman probe technology, qualitative typing detection is carried out on the human red blood cell RHCE gene, and compared with a traditional method, higher sensitivity, higher experiment speed, higher accuracy and a wider application range are shown.

The invention provides an instruction data matching experiment method, system and device and a storage medium, and belongs to the technical field of artificial intelligence, and the method comprises the steps: determining each data set participating in the fine tuning of a large model, setting the parameters of a genetic algorithm, and randomly generating an initial population; each individual in the initial population is used for fine tuning training of a large model; evaluating the large model after fine tuning training to obtain a fitness value corresponding to each individual; selecting an individual with the highest fitness value for generating a next-generation population; pairing the selected individuals, and performing crossover operation according to a set crossover probability; performing gene variation on newly generated individuals according to a set variation probability to generate a new generation of population; and replacing the current population with a new generation of population generated through genetic manipulation, repeatedly executing the steps until a set termination condition is reached, and outputting an individual with the highest fitness value in the new generation of population to obtain an optimal matching scheme. The data matching efficiency is improved, and the labor cost is reduced.

The present disclosure provides methods, compositions and systems for identifying variant targets of interest, for example, in clinically actionable genes. Disclosed herein are representative assays for identifying gene variants, for example, that are implicated in one or more drug metabolism pathways. The methods, composition and systems disclosed herein enable a highly streamlined and cost-effective workflow for moving forward the emerging field of personalized medicine and related fields of study such as pharmacogenomics.

The present disclosure provides a method and a gene detection panel for evaluating treatment response, recurrence and survival by detecting genetic variants and their changes before and after concurrent chemoradiotherapy in tumor tissues of patients with esophageal cancer. The present disclosure develops a set of esophageal cancer NGS analysis panel. Aiming at 402 mutation sites including 35 genes that frequently occur in esophageal squamous cell carcinoma tissue cells, 62 pairs of esophageal squamous cell carcinoma tissues before and after CCRT are analyzed for specific site variation, hoping to find new predictive markers. The present disclosure combines these potential markers into an esophageal cancer detection panel, which has extremely high value for improving the prognosis of esophageal cancer.

The invention relates to a double-gene rare variation and disease relevance prediction model and an establishment method and application thereof, and belongs to the technical field of biological medicines.The establishment method of the double-gene rare variation and disease relevance prediction model comprises the following steps that S1, a sample library is screened; s2, performing quality control on whole exome sequencing data (WES); s3, performing phenotype screening; s4, performing grouping design; s5, carrying out PheWAS logistic regression analysis; s6, performing Firth logistic regression analysis and verification; and S7, carrying out double-gene feature analysis and double-gene pathogenicity relevance prediction. The method for analyzing the correlation between the rare double-gene variation and all disease phenotypes is designed for the first time, and a new method is provided for screening hereditary pathogenic factors of various diseases.

The invention discloses a method and a system for auxiliary determination and grading of brain glioma, and belongs to the technical field of biological genes and bioinformatics. The method comprises the following steps: acquiring sample information of a patient and preprocessing a sample; carrying out FISH detection, NGS detection auxiliary biological information analysis and pathological detection on the sample to respectively obtain N1 FISH detection indexes, N2 NGS detection indexes, N3 pathological detection indexes and gene variation phenomenon characteristics corresponding to the detection indexes; and judging the type and classification of the brain glioma based on the detection indexes and the gene variation phenomenon characteristics corresponding to one or more of the detection indexes. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium, the NGS sequencing technology is used for replacing a part of conventional FISH detection modes, meanwhile, NGS data are reserved, secondary analysis is carried out through a signal generation method to obtain guide newly-added molecular indexes, the detection types and times are reduced, and the detection modes are optimized.

Various embodiments relate generally to the field of nucleic acid amplification and detection, in particular loop-mediated isothermal nucleic acid amplification and the detection of amplicons using designed detection probes. Moreover, various embodiments also relate to methods and kits for determining the presence or quantity of point mutations in a target nucleic acid molecule in a sample using loop-mediated isothermal amplification, which may be used for identifying genetic variants. In one aspect, the detection probe is a single-stranded probe comprising a nucleotide sequence fully complementary to a nucleotide sequence of the probe binding site comprising the point mutation. In another aspect, the detection probe comprising a nucleotide complementary to the point mutation at the penultimate base relative to the 3′ end of the detection probe.

The invention provides a gene variation detection method and device, electronic equipment and a storage medium. The gene variation detection method comprises the following steps: acquiring first long read length sequencing data of a to-be-detected sample, and comparing the first long read length sequencing data with a reference genome to obtain first comparison data; determining a region of the target gene in the reference genome, and calculating a first sequencing depth of the target gene according to the determined region and the first comparison data; determining a first base distribution ratio of the first sub-target gene to the second sub-target gene, and calculating a first sub-sequencing depth of the first sub-target gene and a second sub-sequencing depth of the second sub-target gene according to the first base distribution ratio and the first sequencing depth; and calling a pre-trained detection model to perform copy number variation detection based on the first sub-sequencing depth and the second sub-sequencing depth to obtain a target copy number variation type of the to-be-detected sample. According to the embodiment of the invention, the accuracy of gene variation detection can be improved.

The invention relates to a pathogenic gene identification method and system based on multi-agent debate and a medium. The method comprises the following steps: acquiring gene detection data and clinical phenotype data; the data agent processes the acquired data, and calls a gene variation pathogenicity analysis operator and a molecular genetic large model to obtain first pathogenic gene information; the knowledge agent calls a molecular genetic large model to obtain second pathogenic gene information based on the first pathogenic gene information; the knowledge and data agents sequentially speak and debate pathogenicity of candidate pathogenic genes in the first or second pathogenic gene information on the basis of sorting results in the pathogenic gene information output by the knowledge and data agents; after each round of debate is finished, the debate agent judges whether the sorting results of the data and the knowledge agent on the candidate pathogenic genes are consistent or not, if the sorting results are consistent or the number of debate rounds reaches a threshold value, debate is finished, the debate agent conducts reasoning and outputs a result, and if not, the next round of debate is started. Compared with the prior art, the method has the advantages of no dependence on large-scale training data, high interpretability and the like.

The invention discloses a rice mutant gene and an identification method. Compared with an OsNRAMP5 gene sequence of an indica rice Shuhui 498 genome, the OsNRAMP5 mutant gene of the rice is subjected to base A deletion mutation at the downstream + 1083 site of an initiation codon ATG. The invention creatively proposes that groups are firstly grouped, grouping screening of OsNRAMP5 gene variants is carried out by utilizing high-throughput targeted sequencing of seed endosperm mixed sample DNA, and then only seeds of a variation group in which the screened variant mixed sample DNA with the highest mutation possibility is located are sown into seedlings. And subsequently screening and identifying single plants carrying corresponding variation in the variation group according to single plants. The technology can greatly save the cost of time, land, reagents and the like, and improves the screening efficiency and land utilization efficiency. The method disclosed by the invention is high in efficiency, good in accuracy, simple and convenient to operate, capable of better realizing high throughput, low cost and operation convenience, and suitable for popularization and application.

The present invention discloses the application of TMPRSS9 gene in the diagnosis and treatment of venous thromboembolism, and belongs to the field of medical diagnosis and treatment technology. The present invention verifies the association between missense mutations of TMPRSS9 gene and thrombophilia in human population, in vivo and in vitro, and draws the following conclusions: nonsense mutations and missense mutations at the sites of c.334C>T, c.692C>T, c.917G>A, and c.1709C>T of TMPRSS9 gene are representative in the effect of TMPRSS9 gene mutation on the occurrence of venous thrombosis. The discovery of the above-mentioned pathogenic gene mutations can prevent and treat thrombophilia at an early stage, which is of great significance for the diagnosis, treatment and management of thrombophilia. At the same time, the inclusion of the new TMPRSS9 gene enriches the genetic variation spectrum of venous thromboembolic diseases, which is of guiding significance for the screening of diseases.

Described herein are methods for the identification and detection of genetic factors in the molecular pathways associated with vascular retinopathies or retinal diseases, for example mild, moderate or severe retinopathy of prematurity (ROP). Included herewith are methods of detecting genetic mutations associated with severe retinopathies, including factors in ADRβ2 pathways, which include RAPGEF3, ADCY7, ADCY9, PRKARIA, and ADCY4 variants. Further, this disclosure provides for methods of treating a subject having a detected genetic factor indicative of ROP.

The invention relates to the technical field of data analysis and interpretation, in particular to a colorectal cancer genetic data analysis and interpretation system, which comprises the steps of collecting various types of genetic data from a colorectal cancer patient, performing primary processing, identifying gene variation and biomarkers related to colorectal cancer, and analyzing and interpreting the colorectal cancer genetic data. The method comprises the following steps of: extracting potential genetic characteristics and correlation between the potential genetic characteristics and colorectal cancer onset risks, performing function annotation and interpretation on identified gene variation and biomarkers, and generating personalized treatment suggestions, including targeted treatment schemes, drug selection and prognosis prediction. According to the invention, the specific effect of the gene in colorectal cancer pathogenesis and the influence of the gene on disease progression are deeply analyzed, a targeted treatment scheme, drug selection and prognosis prediction are generated, and precise medical development of colorectal cancer is promoted. The high efficiency and accuracy of the system significantly improve the quality of genetic data analysis, and an important innovative tool is provided for early diagnosis, prognosis evaluation and personalized treatment of colorectal cancer.

The present disclosure relates to genetic copy number variation (CNV) detection. Particularly, aspects are directed to sequencing nucleic acid obtained from a biological sample obtained from a subject to generate sequencing data. The sequence reads are ordered by mapping the sequence reads to a reference genome and stored in an ordered format, A global segmentation of the target region is performed based on the stored sequence reads and a set of segments of the target region is identified and used to determine a copy number variation (CNV) metric. A first status of a genetic condition for the subject is determined based on the CNV metric, and a report of the corresponding genetic condition screening test is determined based on the CNV metric and the status.

The present disclosure provides systems and methods to detect somatic or germline variants by providing a predetermined genomic DNA (gDNA) to an assay mixture, and capturing a sample of a subject's genetic information using a DNA sequencer and detecting genetic variants from the genetic information. A mutation may then be classified as being from a germline source if gDNA derived molecules have lengths inconsistent with those expected from cell-free DNA (cfDNA) derived molecules.

The present invention concerns selective renal denervation treatment of drug resistant hypertensive patients by correlating the patients' genetic panel by categorization and hierarchy according to patients' genetic variants within the functional genes for heart activity, for the renin-angiotensin aldosterone system, and for renal activity.

Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragments from circulating cell free nucleic acid. Also provided herein are methods for partitioning one or more genomic regions of a reference genome into a plurality of portions according to one or more features.

The invention discloses a method and a system for assisting in inputting clinical information of rare diseases and analyzing gene mutation based on phenotypes. The method comprises the following steps: firstly, acquiring clinical information in voice, text and image forms of a patient through a multi-source data acquisition module, converting the clinical information into characters, and performing entity recognition and standardization processing to generate structured medical record data; secondly, extracting clinical phenotypes from the structured data; furthermore, a candidate gene list is obtained according to the gene-disease relationship, comprehensive scoring and sorting are carried out, and a concerned gene list is output. According to the method, efficient structured input and standardization of clinical information are realized, the accuracy and automation level of phenotype-gene matching are remarkably improved, the gene variation interpretation period is effectively shortened, and intelligent support is provided for precise diagnosis of genetic diseases.

Provided herein are methods related to detecting genetic and epigenetic information in a single workflow, as well as methods of treatment, uses, systems, and computer readable storage media related thereto. These methods allow, e.g., for detection of genetic variants and epigenetic modifications (e.g., methylation level) in a single workflow and / or from a single sample (e.g., a DNA sample).

The embodiment of the invention provides a gene variation detection method and device, electronic equipment and a storage medium, and belongs to the technical field of gene variation detection. The method comprises the following steps: fusing a long read length variation detection result and a short read length variation detection result of a to-be-detected gene segment; for the gene loci with inconsistent sequencing results, firstly detecting whether the gene loci are in a genome complex region or not, and if the gene loci are in the genome complex region, determining a variation detection result of the gene loci based on a long-read-long variation detection result; and if not, determining the variation detection result of the gene locus based on the short-read-long variation detection result. The method can improve the accuracy of genome variation detection of the to-be-detected gene segment.