26 results about "Risk gene" patented technology

The invention relates to the technical field of power communication network security, in particular to a power communication network risk assessment method based on risk genes and a space-time large model. According to the technical scheme, the power communication network risk assessment method based on the risk gene and the space-time large model comprises the following steps that equipment sensor data, meteorological grid data and service topology data of a power communication transmission network are obtained in real time through a multi-source data acquisition module, and space-time alignment and feature coding are executed; a risk gene map is constructed, the risk gene map comprises a three-layer map structure of an equipment vulnerability gene, an environment threat gene and a business dependence gene, and a cross-space-time risk propagation rule is defined; a multi-modal space-time large model is trained, and a framework combining Transform and a space-time diagram convolutional network is adopted. A biological gene concept is introduced into power communication network risk assessment, gene-level fault traceability is achieved, and risk factors have combinability and interpretability.

The invention relates to the technical field of assisted reproduction polygene detection, and discloses an oocyte occurrence and maturation disorder detection panel, a detection kit and application thereof, and the detection panel comprises mutation genes related to the oocyte occurrence and maturation disorder for detection, copy number variation genes and rearrangement event and deletion genes. According to the application, by detecting high-risk genes and mutation sites, the risk of occurrence and maturation disorder of the oocytes is predicted in combination with clinic, the development potential of the oocytes is evaluated, the in-vitro maturation strategy is optimized, and the clinical outcome of assisted reproduction is improved. The detection panel can be used for efficiently detecting gene mutation which has clinical diagnosis and treatment significance on oocyte occurrence and maturation disorders; the method has important guiding significance on genetic counseling, risk prediction, clinical diagnosis, precise treatment and potential personalized intervention measures of patients suffering from recurrent oocyte occurrence disorder, oocyte maturation disorder and low oocyte maturation rate and patients to be subjected to assisted reproduction technology treatment.

The invention discloses a joint detection kit for genetic risk genes and medication genes of Alzheimer's disease and a multivariable risk assessment model. The kit comprises a detection reagent for detecting 25 mutation sites of 15 genes, wherein the 25 mutation sites of the 15 genes comprise 17 mutation sites of 10 risk genes and 10 mutation sites of 6 medication genes. Amplification primer pairs and single-base extension primers of each site are designed for 25 mutation sites of 15 genes, multiple PCR amplification and single-base extension reactions are carried out, and the genotype of each site of a product is analyzed by using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. A multivariable risk assessment model for the Alzheimer's disease is constructed by taking a genetic risk score GRS, age, gender and plasma p-tau217 concentration of a risk gene mutation site as markers, one-stop detection of'early screening and medication guidance 'can be realized in combination with a medication gene detection result, and the application prospect and demand are broad.

The application provides a non-coding mutation-induced risk gene expression up-regulation and down-regulation prediction method and system, comprising the following steps: step 1, obtaining a data set and performing pretreatment; step 2, information input standardization between non-coding mutations and gene transcription start points TSS; step 3, non-coding mutation information input standardization; step 4, sequence length alignment and representation learning framework; and step 5, embedded feature merging and prediction output. The application is matched with chromatin accessibility sequencing data to migrate to any tissue or cell type, make accurate and reliable prediction, and utilize an attention mechanism to endow the model with interpretability.

This invention relates to the field of gene polymorphism detection technology and discloses a venous thrombosis risk gene detection kit based on LAMP technology. The kit includes primers and probes for detecting polymorphic sites in venous thrombosis risk genes, detection reaction system components, reagent A and reagent B, positive control A, positive control B, and a negative control. Reagent A and reagent B respectively contain matched primers and probes and the detection reaction system components. Reagent A is a 4G, C, AAG, G, or T reaction tube, and reagent B is a corresponding 5G, T, del, A, or C reaction tube. This invention avoids interference between primers and probes by physically isolating reactions of different nucleic acid sequences in independent reagents A and B. Simultaneously, it utilizes polymerase and cresol red to convert changes in system components into color changes, achieving simultaneous visualization and accurate genotyping of multi-target amplification signals without instrument assistance.

The application relates to the technical field of biomedical engineering, and particularly discloses a method for extracting binary condensate immune signals, which comprises the following steps: screening disease-related high-expression genes by using a disease model, a normal model and a drug treatment model; screening important protein molecules based on the high-expression genes by using a nucleic acid-protein affinity analysis method; constructing a fusion carrier based on cytoskeleton proteins, important protein molecules and green fluorescent protein tracing; and identifying risk genes and possible downstream proteins associated with condensates by spatial omics imaging based on the fusion carrier of the disease model, the normal model and the drug treatment model, and quantifying the condensation process of the condensates. The application reduces the influence of problems such as condensate state destruction and spatial distribution information loss, and accurately realizes in-situ spatial omics imaging and analysis of an immune microenvironment evolution process of a complex disease.

The invention discloses a test case generation method and system, electronic equipment and a storage medium. The method comprises the steps that files of historical production problems are recognized through a natural language processing model, and labels of all target dimensions are extracted; wherein the target dimension at least comprises a trigger module, a trigger scene, root cause analysis, a test key point and a solution; constructing a problem evolution knowledge graph based on the risk genes by using the tags; wherein the risk gene is an essential feature set of historical production problems and is composed of technical gene defects and business logic genes; when a new project exists, semantic analysis is carried out on the demand file of the new project through a BERT model, and demand information of the new project is obtained; retrieving risk genes and solution information corresponding to the new project from the problem evolution knowledge graph based on the demand information of the new project; and generating a test case of the new project by using the retrieved risk gene and the solution information corresponding to the new project.

The invention provides a teenager myasthenia gravis eye muscle type-whole body type transformation risk prediction marker and application thereof. Through GWAS analysis and research, two risky gene regions related to the transformation of the adolescent pure eye muscle type myasthenia gravis to the whole body type are obtained, and single nucleotide polymorphism (SNP) sites with statistically significant association are successfully identified.

The invention discloses guideRNA (Ribonucleic Acid) of a targeted mouse Gba gene, the guideRNA is designed according to the eleventh exon of a mouse Gba-202 transcript, and the nucleotide sequence of the guideRNA is as shown in SEQ ID No. 1. The invention also discloses a construction method of the Parkinson's mouse model and application of the construction method in research on pathogenesis of primary Parkinson's disease. The invention provides an innovative and reliable construction method of the Parkinson's mouse model through the combined action of a PD risk gene Gba mutant mouse and a high milk diet dangerous environment, and the constructed Parkinson's mouse model can better simulate the occurrence and development process of PD, conforms to the pathological progress of PD progressive aggravation, can monitor the early change of PD, and has a good application prospect. And the model can dynamically quantify the dyskinesia and pathological progress of the PD, and can provide a research basis for different stages of PD.

The invention provides for the detection of a perturbed gene network, which includes highly expressed genes during fetal brain development, which is dysregulated in neuron models of autism spectrum disorder (ASD). High-confidence ASD risk genes are upstream regulators of the network modulating RAS / ERK, PI3K / AKT, and WNT / / β-catenin signaling pathways. The invention demonstrates how the heterogeneous genetics of ASD can dysregulate a core network to influence brain development at prenatal and very early postnatal ages and, thereby, the severity of later ASD symptoms. The invention provides a model for diagnosis, prognosis determination, and optionally treatment and monitoring, for any disease by comparing molecular marker patterns in non-affected tissues in a subject with healthy controls to determine a dysregulated network in the subject based on a co-expression pattern of interacting genes.

The application is suitable for the technical field of tumor identification, and provides a tumor heterogeneity identification method, device, electronic equipment and storage medium. The application firstly locates tumor risk genes with consistency change, then identifies subclone specific genes related to tumor risk gene expression, determines subclone specific genes related to survival of a patient to a specified correlation degree, performs consistency clustering analysis on sample patients to obtain a classification label, constructs an optimal tumor prognosis model and screens an optimal image genome feature according to the tumor MRI image and the classification label of the sample patient, and finally analyzes an external tumor MRI image through the optimal tumor prognosis model and the optimal image genome feature, so that tumor heterogeneity quantitative analysis is realized on the premise that the patient is not caused trauma, the survival time of a tumor patient is predicted only through the tumor MRI image, and important theoretical basis and application value are provided for tumor precision medicine.

The application discloses a construction method of a mouse model with increased transcription factor FOXG1 copy number and application thereof, belongs to the field of animal models, and is characterized in that FOXG1 syndrome is caused by mutation of a risk gene FOXG1, and the increased copy number makes FOXG1 expression up-regulated as one of the mutation forms. FOXG1 up-regulation is also found in some autism patients. The construction method of the mouse model with increased FOXG1 copy number comprises plasmid construction and microinjection of CAG-loxp-stop-loxp-Foxg1-IRES-EGFP, F0 generation Founder mouse identification, and F1 generation mouse stable genetic genotype identification. The application over-expresses a mouse Foxg1 gene, simulates the increase of the FOXG1 syndrome clinical case copy number and the up-regulation of FOXG1 in autism patients. The application can provide a model for autism research and be used for developing precise diagnosis and intervention strategies for the FOXG1 syndrome.

The invention discloses a candidate drug screening method and system based on gene drug interaction, a medium and equipment, and belongs to the technical field of biomedicines.The method comprises the steps that an abnormal gene data set of a deafness patient is obtained, a deafness gene-candidate drug relational database is input for matching, and corresponding candidate drugs are obtained; the database construction process comprises the following steps: acquiring a deafness risk gene data set, a drug-target gene network and KEGG pathway data; mapping the deafness risk genes to a drug network to obtain a drug-deafness risk gene network; analyzing the KEGG pathway to obtain a gene regulatory network; mapping the drug target genes to the regulatory network, and retaining a drug-pathway relationship containing at least two target genes; and screening drugs consistent with the deafness risk genes and related genes in regulation direction and pathway as candidate drugs, and constructing a database. Therefore, by implementing the method, the problem that candidate drugs screened based on individual abnormal genes in the prior art are lack of pathway-level biological mechanism support and are insufficient in pertinence can be solved.

The invention provides a human venous thrombosis risk gene polymorphism detection primer probe composition as well as preparation and application thereof, and belongs to the technical field of nucleic acid detection methods. The primer probe composition comprises the following sequences: a primer pair PAI-1-F and PAI-1-R which are used for detecting the PAI-14G / 5G site and are respectively shown as SEQ ID NO: 1 and SEQ ID NO: 2, and a probe PAI-1-P of which the sequence is shown as SEQ ID NO: 3; the probe is used for detecting PROCc.565Cgt; the primer pair of the T site PROC (565 Cgt; t)-F and PROC (565 Cgt; the invention relates to a kit for detecting the content of procyanidine, in particular to a kit for detecting the content of procyanidine, which comprises a probe PROC (565Cgt, T)-R and a probe PROC (565Cgt; t)-P, the sequence of which is as shown in SEQ ID NO: 6; the detection kit is used for detecting MTHFRc.677Cgt; the sequences of the primer pair MTHFR-F and MTHFR-R of the T site are respectively shown as SEQIDNO: 7 and SEQIDNO: 8, and the sequence of the probe MTHFR-P is shown as SEQIDNO: 9; wherein the 5'end of the probe is marked with a fluorophore, the 3 'end of the probe is marked with a quenching group, and the first three basic groups are modified by phosphoric acid. The kit is high in detection sensitivity.

This invention provides a probe library and kit for detecting genetic risk gene mutations in viral infections, belonging to the field of gene detection technology. The probe library and kit designed in this invention achieve, for the first time, the simultaneous detection of all mutations in the following 51 genetic risk genes for viral infections: CARMIL2, CCL2, CD27, CD70, CIB1, CTPS1, CXCR4, CYBC1(C17orf62), DBR1, FCGR3A, FCHO1, ICAM1, IFIH1, IFNAR1, IFNAR2, IFNGR1, IFNGR2, IL10, IL10RA, IL10RB, IL... The probe library and kit of this invention contain 18BP, IRF3, IRF7, IRF9, MAGT1, LIG1, MCM2, NOS2, OAS1, POLR3A, POLR3C, POLR3F, PRKCD, RASGRP1, SH2D1A, STAT1, STAT2, TBK1, TICAM1, TLR3, TLR7, TLR8, TMC6, TMC8, TNFRSF9, TRAF1, TRAF2, TRAF3, TYK2, UNC93B1, and XIAP. This invention's probe library and kit can be used for detecting genetic variations in the risk of viral infection in clinical settings, assessing an individual's genetic risk of viral infection, and has broad application prospects.

The application discloses a method for identifying and evaluating schizophrenia risk structural variations based on third-generation sequencing, relates to the field of molecular biology, and performs whole genome sequencing on peripheral blood DNA of a patient through third-generation sequencing, adopts multi-tool joint detection, integrates multi-sample results, and generates a high-confidence SV data set; through cross-queue comparison, patient-specific SV is screened, and high-risk potential pathogenic SV is identified in combination with an SV prioritization tool, SVJudge; transcription factor binding analysis, SCZ drug target data and tissue cell-specific expression data are combined to evaluate the influence of SV on gene regulation and analyze the potential action mechanism of SV in SCZ. SCZ risk genes are screened based on SVJudge scores and patient carrying conditions, the genetic risk and pathogenic mechanism of the SCZ risk genes are verified through pathway enrichment, protein interaction network and functional module analysis, and a new technical means and theoretical basis are provided for genetic research of SCZ.

The invention relates to the technical field of assisted reproduction polygene detection, and discloses an ovarian dysfunction detection panel, a detection kit and application of the ovarian dysfunction detection panel. The detection panel includes mutation genes, copy number variation genes, and rearrangement event and deletion genes associated with ovarian dysfunction (including one or more of hypoovarian reserve function (DOR), premature ovarian insufficiency (POI), polycystic ovarian syndrome (PCOS), and hypogonadotrophy gonadotrophy hypofunction (HH)) for detection. According to the application, the risk of patients suffering from DOR, POI, PCOS and HH and the risk of ovarian dysfunction can be accurately evaluated by detecting the high-risk genes. The method has important guiding significance on clinical diagnosis, risk prediction, genetic counseling and precise treatment of ovarian dysfunction, DOR, POI, PCOS, HH and patients to be treated by an assisted reproduction technology, and improvement of clinical outcome of assisted reproduction.

This invention discloses an artificial intelligence-based method and system for assessing network security level protection. Relating to the field of internet security technology, this invention extracts key operations through time-granular adaptive slicing, traces the triggering, propagation, and influencing sub-genes in reverse, and constructs a risk gene chain. It calculates propagation power scores based on an asset resistance matrix, defines the risk impact range using an elastic boundary radius, and dynamically adjusts it. Finally, it dynamically adjusts thresholds by combining network environment factors and similarity with the gene chain library to classify security risk levels. This invention improves the automation and dynamic adaptability of the assessment, enhances the accuracy of risk assessment, and provides effective support for network security protection.

The present invention provides a method, device, medium, and program product for identifying disease risk elncRNAs and risk genes, relating to the field of intelligent medicine. This application provides a process, SCZ-elnc, for identifying risk elncRNAs and their target genes driven by disease GWAS signals by integrating the following two steps: (1) identifying risk elncRNAs by combining risk SNPs, eQTL data, and enhancer elements in genomic locations; and (2) predicting genes regulated by elncRNAs using multiple supporting evidence from transcriptomics and epigenomic data.

The present application relates to a gene detection primer and evaluation model for recurrent miscarriage risk caused by thrombosis, and belongs to the field of molecular biology and bioinformatics, in particular: based on multiple PCR amplification and capillary electrophoresis detection of multiple SNPs, and through the construction of a regression prediction model, different weights are given to the included SNP sites, scoring, and finally classifying and evaluating the thrombosis risk of the sample to be tested. The present application discloses a gene for recurrent miscarriage risk caused by thrombosis, including 11 gene names and 12 corresponding sites set, and primers corresponding to the 12 sites. The present application also discloses an evaluation model for recurrent miscarriage risk caused by thrombosis and a corresponding evaluation model.

The invention provides a chronic obstructive pulmonary disease susceptibility gene combination detection micro-fluidic chip and an evaluation scheme, and the disease risk level is prompted for screened positive people, so that the risk people can find clinical means for detection or intervention before the disease is attacked. According to the scheme provided by the invention, effective screening of risk genes can be ensured, the micro-fluidic chip is adopted as a detection carrier, the screening mode is flexible, the manual requirement is low, and development of common medical units is facilitated.

The present application relates to the fields of biological medicine and data analysis, and particularly relates to a screening method and system of Alzheimer's disease diagnostic markers. The present application provides a screening method and system of Alzheimer's disease diagnostic markers, based on Mendelian randomization (SMR) analysis of aggregated data, combined with multi-omics (risk gene methylation, expression and protein abundance information) research methods, to find key genes in AD pathology, and to reveal their regulatory mechanisms in AD pathogenesis. The method and system provided by the present application further refine the AD diagnostic markers and therapeutic targets, deepen the understanding of the molecular mechanisms in AD disease, find new therapeutic targets, provide innovative strategies and tools for individualized treatment, and ultimately improve the quality of life of patients.

The application discloses a gene-phenotype correlation analysis model and a method and application thereof, and belongs to the technical field of biological medicine. The model establishment method comprises the following steps: S1, collecting known trait-gene data to form a gene-trait pair; S2, calculating the rare mutation type score of each gene by using a formula; S3, analyzing the correlation between the mutation score and the trait by linear regression, calculating the weight of each mutation type, and optimizing the weight combination, so that the correlation R 2 is taken as the evaluation standard; S4, calculating the rare mutation load score of a sample gene according to the scoring formula and the optimized weight; S5, analyzing the correlation between the mutation load score and the phenotype by a regression method, and constructing a gene-phenotype correlation analysis model. Compared with a traditional gene-base collapsing method, the model has good reproducibility and complementarity, and can be used for discovering candidate risk genes of new traits or unknown diseases.

The invention discloses application of echinacoside in treatment of schizophrenia. The method belongs to the field of medicines and comprises the following operation steps: screening schizophrenia risk genes; constructing a gene editing mouse model; evaluating a behavior normal form; predicting a protein structure; molecular docking; and carrying out behavioral pharmacology experiments. According to the echinacoside disclosed by the invention, in schizophrenia treatment, a healthy control mouse model and a schizophrenia mouse model are respectively subjected to intraperitoneal injection drug treatment for two weeks, and then the influence of echinacoside treatment on the schizophrenia mouse behavior phenotype is evaluated through a behavioral experiment. The pharmaceutical composition disclosed by the invention has a good treatment effect in the aspects of negative symptoms of schizophrenia, cognitive impairment and sensory gating defect, and a new drug target and a new treatment approach are provided for the treatment of schizophrenia.

The application provides a method for predicting intrahepatic cholestasis of drugs based on multi-dimensional feature modeling. The application collects risk genes of intrahepatic cholestasis, collects positive and negative drugs of intrahepatic cholestasis and their targets, establishes a disease onset cluster of intrahepatic cholestasis, calculates the relative average shortest distance of the disease onset cluster and the drug target in the network to obtain network topology features, identifies the structural alarm of intrahepatic cholestasis and calculates the Mordred descriptor of the drug molecule to obtain molecular structure features, uses a machine learning algorithm for modeling and prediction, and finally uses a deep learning method to represent the definition domain of the model. Compared with the traditional method, the application integrates bioinformatics analysis technology by using big data artificial intelligence, characterizes the drug from the molecular structure and disease onset, provides a new method and new idea for the complex toxicity prediction of drugs.

The invention discloses a network security level protection evaluation method and system based on artificial intelligence, and relates to the technical field of internet security, and the method comprises the steps: extracting key operation through time granularity adaptive slicing, reversely tracing, triggering, spreading and influencing sub-genes, and constructing a risk gene chain; calculating a propagation force score based on the asset resistance matrix, framing a risk influence range through an elastic boundary radius, and performing dynamic adjustment; and dynamically correcting a threshold value in combination with a network environment factor and the similarity between the network environment factor and the gene chain library, and dividing security risk levels. According to the method, the automation and dynamic adaptability of evaluation are improved, the accuracy of risk evaluation is enhanced, and effective support is provided for network security protection.