173 results about "Gene Variant" patented technology

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.

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 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 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 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 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.

The invention relates to the field of gene detection, and particularly discloses a gene detection device and method applying Beidou satellite positioning, and the device comprises a sample collection and preprocessing module which is used for obtaining a body fluid or tissue biological sample of a user, and carrying out cell lysis, DNA / RNA extraction and purification operation on the sample; the gene sequencing analysis module is connected with the sample collecting and preprocessing module and is used for performing gene sequencing on the purified nucleic acid sample and identifying gene variation information related to tumors; the high-precision positioning capability of the Beidou system is utilized to obtain the environmental parameters of the geographic position of the user in real time, then the genetic variation data and the regional environmental carcinogenic factors are subjected to weighted fusion analysis through the risk assessment algorithm, and finally a highly personalized detection report is generated. In this way, the detection result can truly reflect the specific influence of the external environment on the individual health, and the accuracy and practicability of the report are remarkably improved.

Methods for detecting a short genetic variant in a test sample are described herein. In some exemplary methods, the short genetic variant is called using one or match scores, which are determined using one or more sequencing data sets obtained from a test nucleic acid molecule, wherein the test sequencing data sets are determined by sequencing the test nucleic acid molecule using non-terminating nucleotides provided in separate nucleotide flows according to a flow-cycle order. Also described herein are methods of sequencing a test nucleic acid molecule using two or more different flow-cycle orders and / or extended flow cycle orders having five or more nucleotide flows per flow cycle.

Provided herein are computer-implemented methods for assigning maternal or fetal origin to one or more genetic variations in cell-free DNA (cfDNA) of a sample from a pregnant mammal, preferably a pregnant human, it uses a probabilistic model for assigning maternal or fetal origin to genetic variations in DNA from a sample obtained from a pregnant mammal, where the model assigns maternal or fetal origin based on a combination of fetal fraction and DNA fragment size.

The application belongs to the technical field of gene detection, and discloses a method and system for judging the influence of homologous regions in NGS gene variation detection. The method comprises the following steps: obtaining a first type of gene and a plurality of second type of genes according to a public database; obtaining corresponding original sequence files of the first type of gene and the second type of gene based on a local gene database, obtaining corresponding sequence alignment files based on a local BAM database, and combining them to obtain known NGS gene data; calculating the GC content, the proportion of repeat units, and the similarity ratio in the original sequence file, and calculating the alignment quality in the corresponding sequence alignment file to construct a training sample; inputting the training sample into a classification model to obtain an optimized classification model; extracting the GC content, the proportion of repeat units, the similarity ratio, and the alignment quality from the NGS gene data to be detected and inputting them into the optimized classification model to judge whether the variation detection is affected. The application can judge the influence of homologous regions in variation detection without the aid of prior information of homologous regions.

Described herein are methods for making genetically modified cells by introducing combinations of genetic variants (designed or random) or constructs (genes or otherwise arbitrary DNA) into a population of cells, and for tracking each variant combination by sequentially building an array of barcodes at a common locus (chromosomal or plasmid), termed the barcode locus. Also described are the cells made by such methods.

The invention relates to a computer-implemented method for determining pharmacogenetic star alleles from high-throughput sequencing data, the method comprising the following steps: providing a plurality of result files which have been output by a plurality of different computer programs for genotyping and which each have a plurality of result elements, wherein each result element has at least one gene designation; shortening the allele designation as far as possible on the right for each result element of the plurality of result elements from each result file of the plurality of result files; and outputting the gene designation and a specific result diplotype. The invention also relates to a computer-implemented method for determining rare genetic variants. Finally, the invention also relates to a device having a processor and a memory in order to carry out such methods.

The application relates to the technical field of gene variation detection, in particular to a copy number variation detection method based on semi-supervised learning. The method comprises the following steps: obtaining read depth signals and mapping quality signals of each normal window of a reference genome sequence from alignment information of sequencing reads, correcting the read depth signals of all normal windows in terms of GC content bias, adopting a cyclic binary segmentation algorithm to divide all normal windows into segmented regions with uniform read depth signals, identifying copy number variation breakpoint positions in combination with a split read strategy, performing normalization processing on the mapping quality signals, performing smoothing and noise reduction processing on the read depth signals, labeling pseudo labels for corresponding segmented regions, performing clustering analysis on all segmented regions through an improved density clustering algorithm, integrating and determining the variation types of abnormal segmented regions, and outputting copy number variation detection results, so that efficient detection of copy number variation is realized, and the accuracy and reliability of the detection results are significantly improved.

Systems and methods herein provide for rapid patient information to healthcare providers such that the healthcare providers can make more informed diagnoses. One method includes storing gene sequencing data and called genetic variants of a patient in a data structure. The method also includes receiving a request from a healthcare provider for results of a test that reports at least a portion of the called genetic variants in relation to a diagnosis of the patient by the healthcare provider, and delivering the results of the test to the healthcare provider if a quality control value of said at least a portion of the called genetic variants meets or exceeds a predetermined threshold of quality for assisting the healthcare provider.

Methods and apparatus for selecting genetic variants for a tumour-informed assay are provided. The method includes receiving a sample collected from a patient, the sample being associated with a cancer type, generating a mutational catalogue for the sample, the mutational catalogue indicating a proportion of genetic mutation types observed in the sample, selecting a set of signatures associated with the cancer type, the set including one or more signatures, each signature comprising a mutational profile, determining, based on the set of signatures associated with the cancer type and the mutational catalogue, a set of genetic variants most likely to be genuine somatic variants associated with the sample, and outputting the set of genetic variants for use in creating a tumour-informed assay for the patient.

Disclosed are methods, systems and computer-program products for the determination of complex genetic variants. The disclosed methods, systems and computer-program products may include obtaining a mutant scaffold nucleotide sequence that comprises a sequence that includes mutations characteristic of the complex genetic variant; obtaining a wild-type scaffold nucleotide sequence having a wild-type sequence; generating an alignment of at least one sequence from the sample to the mutant scaffold and to the wild-type scaffold; and determining that the sample contains a mutation characteristic of the complex genetic variant based on alignment to the mutant scaffold and not the wild-type scaffold.

The present invention relates to a gene variant of the transcriptional regulator LysG and a method for producing L-citrulline or L-arginine using same. The gene variant of the transcriptional regulator LysG according to the present invention has protein activity that is altered due to the mutation of one or more bases in the base sequence of a gene encoding the transcriptional regulator LysG, and thus, it is possible to effectively produce L-citrulline or L-arginine from a recombinant microorganism comprising the variant.

The types of genetic variants detected by NGS are very wide and not all genetic variants always lead to diseases, and thus it is difficult to quickly and accurately interpret the meaning of disease relevance for detected genetic variants. The present invention relates to a method of interpreting genetic variants based on nucleic acid sequencing. The method of interpreting genetic variants according to the present invention provides a logic tree for interpreting NGS variant data, which can classify the pathogenicity of genetic variants based on the ACMG guidelines and determine the level of pathogenicity of the genetic variants, and thus it is expected to be widely used in the life sciences and medical health fields.

An apparatus for generating personalized risk assessments for neurodegenerative diseases includes a computing device that receives user data containing genetic and medical information. It processes the data to create genotype identification and gene detection modules, identifying user genotypes and relevant genetic markers. The user's mitochondrial haplogroup is examined to refine the assessment. A risk calculation module employs machine learning to weigh genetic variants against population-based data, calculating a polygenic risk score (PRS). The PRS forms a personalized risk profile, displayed through a visual interface. The disclosed systems offer a comprehensive approach to accurate risk assessment, enabling targeted interventions and informed decision-making in neurodegenerative disease management.

Presented herein are methods for mapping the effects of gene variants using high throughput sequencing and machine learning to determine the pathogenicity of each variant

The present application relates to a multiplex PCR primer probe combination and kit for human red blood cell RHD gene typing detection, and belongs to the field of biomedical clinical molecular detection. The multiplex PCR primer probe combination for human red blood cell RHD gene typing detection comprises 19 pairs of specific primers and corresponding probes distributed in 8 reaction wells. The present application also provides a kit containing the multiplex PCR primer probe combination for human red blood cell RHD gene typing detection. The RHD gene variant site specific primers and probes designed by ARMS combined with homologous sequence specific base method are more specific and accurate; all high frequency RHD gene variants of Chinese population can be detected by one experiment, including DEL type (RHD*DEL1, c.1227G>A), weak D15 type (RHD*15), partial RHD*DVI.3 type (RHD*DVI.3), RHD deletion type D negative (RHD*01N.01) and other common D negative phenotypes of Chinese population, RHD*D-CE(2-9)-D (RHD*01N.03) and RHD*01N.16 (c.711delC), and normal RHD positive types (RHD*01) can also be detected.

The invention relates to the technical field of gene variation detection, in particular to a copy number variation detection method based on semi-supervised learning. Comprising the following steps: acquiring a read depth signal and a mapping quality signal of each normal window of a reference genome sequence from comparison information of sequencing reads, and performing GC content deviation correction on the read depth signals of all the normal windows; all normal windows are segmented into segmented areas with uniform read depth signals by adopting a cyclic binary segmentation algorithm, and copy number variation breakpoint positions are identified in combination with a read splitting strategy; performing normalization processing on the mapping quality signal; performing smooth noise reduction processing on the read depth signal; labeling pseudo labels for the corresponding segmented areas; according to the method, clustering analysis is carried out on all segmented areas through an improved density clustering algorithm, integration and variation type judgment are carried out on abnormal segmented areas, and a copy number variation detection result is output, so that efficient detection of copy number variation is realized, and the accuracy and reliability of the detection result are remarkably improved.

This invention belongs to the field of biopharmaceuticals and relates to a gene therapy drug for hereditary retinal dystrophy related to RLBP1 gene mutations and its application. Specifically, it involves constructing a recombinant AAV-RLBP1 gene therapy drug, which is then injected intravitreally to infect retinal pigment epithelial cells and Müller cells, causing them to express complete and active RLBP1 protein. This invention utilizes a modified AAV vector to package codon-optimized human RLBP1-cDNA, enabling the expression of complete and active RLBP1 protein, which participates in the visual circulation pathway, rescuing retinal dysfunction caused by pathogenic mutations in the RLBP1 gene, improving visual function in patients, or delaying disease progression.

The invention relates to a primer, a probe composition and a kit for detecting variation sites of KMT2D genes of the Pantoea syndrome, and provides three types of KMT2D gene mutation sites found for the first time so as to enrich the variation spectrum of the KMT2D genes, the three types of variation sites are respectively the variation sites of the KMT2D genes c.3247dup, c.1101611019del and c.15545del, and the variation spectrum of the KMT2D genes is enriched by using the primer, the probe composition and the kit for detecting the variation sites of the KMT2D genes of the Pantoea syndrome, namely the mutation sites of the KMT2D genes of the Pantoea syndrome, of the KMT2D genes of the Pantoea syndrome, of the Pantoea syndrome. Meanwhile, the invention also provides a primer, a probe composition and a kit for detecting the variation site of the KMT2D gene of the Pansheng syndrome. The primer, the probe composition and the kit are used for screening or diagnosing the Pansheng syndrome. The mutation sites are proved to be new pathogenic mutations related to the Pansher syndrome, the KMT2D gene pathogenic variation spectrum is expanded, the kit can comprehensively cover the three new pathogenic variation sites of the KMT2D gene related to the Pansher syndrome, and the three pathogenic variation sites found for the first time can be specifically and accurately detected.

This disclosure is in the field of cardiac diseases. For example, the disclosure provides a new platform comprising iPSC and cardiomyocytes carrying one or more gene mutations, and models to study the effect of those gene mutations on cardiomyocytes, and on drug toxicity. This platform is identified herein as PREDICT PLATFORM.

Systems and methods for estimating tumor fraction in a biological sample are disclosed. One method may include: receiving sequencing data for each of a plurality of biological samples included on a combined targeted sequencing panel, wherein the sequencing data for each of the plurality of biological samples includes: genetic variant sequencing data covering one or more genetic variants of each of the plurality of biological samples; and background sequencing data covering all other genetic variants from all of the other biological samples; calculating, from the background sequencing data associated with each of the plurality of biological samples, a site-specific error rate for each genomic location associated with each of the one or more genetic variants; and establishing, based on the calculated site-specific error rate, a threshold for tumor fraction estimation for each of the one or more genetic variants. Other aspects are described and claimed.

The invention belongs to the technical field of bioinformatics, and discloses a molecular marker screening method and device based on sequencing, equipment and a storage medium. Sample sequencing data is obtained for quality control processing to obtain clean sequencing data, and gene variation sites are obtained through detection; analyzing to obtain a target gene expression map; carrying out weighted gene co-expression network analysis to obtain an analysis result; carrying out co-expression analysis, constructing a miRNA-gene molecule interaction network, carrying out topology analysis on the miRNA-gene molecule interaction network, and identifying key nodes; and finally, according to the gene variation site, the target gene expression map, the analysis result and the key node of the miRNA-gene molecular interaction network, combining with a machine learning algorithm to calculate the importance score of each candidate marker, and obtaining a specified number of candidate markers with top scores and the combination thereof as a target marker. Therefore, the potential efficiency of the marker can be comprehensively evaluated in multiple dimensions, and the specificity and sensitivity of the screened marker are further improved.

The invention relates to a genetic variation category prediction method and device based on convex hull geometric constraint, and relates to the fields of bioinformatics, artificial intelligence, applied mathematics and the like, and the method comprises the steps: obtaining multi-modal data corresponding to target genetic variation, including a target variation DNA sequence, a target reference DNA sequence and target semantic text information; performing feature extraction on the multi-modal data through the trained gene variation category prediction model, and predicting the category of target gene variation; wherein loss functions adopted in the model training process comprise a classification loss function used for indicating the difference between a prediction category and a real category, the convex hull geometric constraint loss function is used for indicating the concentration degree of the same type of gene variation corresponding to the distribution range of the feature space and the separation degree of different types of gene variation corresponding to the distribution range of the feature space. According to the invention, based on multi-modal feature fusion and convex hull geometric constraint, efficient and accurate prediction of the gene variation category is realized.

The invention relates to a multiplex fluorescent quantitative PCR (polymerase chain reaction) primer, a probe and a kit for detecting neurofibroma I type NF1 gene variation sites, and provides four NF1 gene mutation sites found for the first time, the four variation sites are NF1 gene c.21002105delinsAG, c.4561dup, c.6421del and c.6797dup variation sites respectively, and the mutation sites of the NF1 gene c.21002105delinsAG, the c.4561dup, the c.6421del and the c.6797dup can be used for detecting neurofibroma I type NF1 gene mutation sites. Meanwhile, the invention also provides a specific primer, a probe composition and a kit for detecting the NF1 gene variation site of the neurofibromatosis I type for screening or diagnosing the neurofibromatosis I type. The NF1 gene pathogenic variation spectrum is expanded, and a basis is provided for diagnosis and genetic counseling of the neurofibroma type I. The kit disclosed by the invention can comprehensively cover four new pathogenic variation sites of the NF1 gene related to the neurofibroma type I, is high in accuracy, and can specifically detect the pathogenic variation sites.

The invention discloses a multiple myeloma sequencing method based on a targeted capture three-generation sequencing technology, a kit and application, and relates to the technical field of gene detection, and the method comprises the steps of sample treatment, targeted probe group design and targeted enrichment capture, three-generation sequencing library preparation, bioinformatics analysis and the like to identify and analyze three types of variations. According to the method, the defects that an existing layered system lacks an accurate genomics basis, and FISH and NGS technologies and combination strategies are low in flux, incomplete in coverage, incapable of synchronously detecting various variations, high in cost and complex in process are overcome, comprehensive information of three key variation types of multiple myeloma SNV, SV and CNV can be obtained at the same time through a single experiment and one-time sequencing, and the method is suitable for popularization and application. The detection efficiency is improved, and sample consumption, operation time and cost are reduced; all hot spot areas and translocation breakpoint areas of the most important clinical related genes of the MM are covered, and a gene variation map which is more comprehensive than that of a standard FISH Panel is provided.