Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Hiro

60 results about "Computational gene" patented technology

A computational gene is a molecular automaton consisting of a structural part and a functional part; and its design is such that it might work in a cellular environment. The structural part is a naturally occurring gene, which is used as a skeleton to encode the input and the transitions of the automaton (Fig. 1A). The conserved features of a structural gene (e.g., DNA polymerase binding site, start and stop codons, and splicing sites) serve as constants of the computational gene, while the coding regions, the number of exons and introns, the position of start and stop codon, and the automata theoretical variables (symbols, states, and transitions) are the design parameters of the computational gene. The constants and the design parameters are linked by several logical and biochemical constraints (e.g., encoded automata theoretic variables must not be recognized as splicing junctions). The input of the automaton are molecular markers given by single stranded DNA (ssDNA) molecules. These markers are signalling aberrant (e.g., carcinogenic) molecular phenotype and turn on the self-assembly of the functional gene. If the input is accepted, the output encodes a double stranded DNA (dsDNA) molecule, a functional gene which should be successfully integrated into the cellular transcription and translation machinery producing a wild type protein or an anti-drug (Fig. 1B). Otherwise, a rejected input will assemble into a partially dsDNA molecule which cannot be translated.

Transcriptome-based tumor neoantigen identification method

The invention discloses a transcriptome-based tumor antigen identification method. The method comprises four steps of: obtaining an RNA sample of a patient tumor tissue, and carrying out library construction and amplification on the RNA sample to obtain an RNA sample sequencing result of the tumor tissue; aligning short read segments of the RNA sample sequencing result to a human reference genometo obtain an RNA alignment result; calculating gene expression quantity according to the RNA alignment result, and carrying out mutation detection and prediction of fusion gene events according to theRNA alignment result; and predicting transcriptome HLA typing according to the alignment result, wherein calculation of the gene expression quantity, mutation detection and prediction of the fusion gene events are carried out according to a specified order or simultaneously carried out; and using the gene expression quantity of a transcriptome sample, depth of transcriptome mutation sites in a whole-exon sequencing sample and binding force of neonatal short peptides and the patient HLA typing as an analysis result to submit the same to a downstream analyst. The invention provides the method capable of identifying a tumor-specific antigen of an individual sample from tumor patient transcriptome NGS data.
Owner:HANGZHOU NEOANTIGEN THERAPEUTICS CO LTD

Disease-associated gene combination counting method and system

The invention discloses a disease-associated gene combination counting method and system. The method comprises computing the significance of every mononucleotide polymorphic site in a gene sequence through a genome-wide association analysis method, wherein the significance presents the degree of association between the mononucleotide polymorphic site and diseases, acquiring the significance of themononucleotide polymorphic sites; according to the significance and a threshold value, screening out the mononucleotide polymorphic sites associated with the diseases to acquire the associated mononucleotide polymorphic sites; through an extreme gradient-based Boosting ensemble learning method, categorizing people corresponding to the associated mononucleotide polymorphic sites into affected onesand non-affected ones and further acquiring associated gene combinations. By combining the genome-wide association analysis method and the gradient-based Boosting ensemble learning method to categorize people corresponding to the associated mononucleotide polymorphic sites into the affected ones and the non-affected ones and further to acquire the associated gene combinations, the disease-associated gene combination counting method can improve the accuracy of acquired disease-associated gene combination results.
Owner:HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL

Analysis system for gene copy number variation

The invention provides an analysis system for gene copy number variation. The system comprises an analysis module, a division module, a statistics module, a window computing module and a picture module, wherein the analysis module is used to read in an index document and a reference genome of data, and make comparison; the division module is used to divide a sam document of a comparison result of the whole genome according to chromosomes; the statistics module is used for statistics of a comparison result of comparison sequencing data; the window computing module is used to compute an average covering depth of each window on the genome with 1KB as the window, and results are given in the form of a list; the picture module is used to draw a chromosome covering depth picture according to computing results; and the analysis module is a major module which successively calls other modules to complete each part of analysis work. The system provided by the invention has the advantages that the copy number variation on a human genome level can be accurately analyzed by high-throughput sequencing data, and high-resolution pictures can be displayed; and the statistics can be carried out to data comparison information, so that data assessment becomes convenient.
Owner:WANKANGYUAN TIANJIN GENE TECH CO LTD

Intergenic interaction relation excavation method based on Bayesian network reasoning

The present invention provides an intergenic interaction relation excavation method based on Bayesian network reasoning. The method comprises the following steps of: 1, employing a method of estimation of entropy by employing a Gaussian kernel probability density estimation quantity to calculate interaction information between genes, between genes and phenotypic characters and between phenotypes and the phenotypic characters; 2, employing a three-stage dependence analysis Bayesian network structure learning method to construct a Bayesian network including genes and phenotypic character nodes;3, employing the Bayesian estimation parameter learning method to perform parameter learning to obtain a contingent probability form between nodes; and 4, employing a Gibbs sampling Bayesian network approximate reasoning method to calculate the contingent probabilities of genes with different quantities and the phenotypic characters, and obtaining an intergenic interaction relation influencing thespecial phenotypic characters according to the calculation result. The intergenic interaction relation excavation method based on Bayesian network reasoning can help biology researchers of obtainingof epistasis genetic locuses influencing the special phenotypic characters to assist in gene function excavation and provide reference for hereditary basis analysis of complex quantitative charactersof different species.
Owner:HUAZHONG AGRI UNIV

Survival prediction method and system based on image genomics

The invention discloses a survival prediction method and system based on image genomics. The method comprises the following steps: acquiring image data of tumor patients and lifetime data and RNA data of each patient, and establishing a data set; segmenting a tumor area of each patient from the image data; inputting the image data of each patient into a neural network to extract image features and cluster the image features to obtain a plurality of image modules; obtaining a gene module of each patient by using the RNA data; performing screening according to the correlation between the gene modules and the image modules, and selecting a plurality of gene modules and image modules which are strongly correlated; performing pathway enrichment on genes in the selected gene module to obtain a gene pathway related to the image module; calculating a gene set variation analysis score of the gene pathway, and retaining the gene pathway having strong correlation with the image module; and carrying out survival prediction by using the retained image features. According to the invention, the biological interpretability in the aspect of survival prediction can be improved, and the generalization ability of deep learning can be improved at the same time.
Owner:SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI

CRISPR/Cas9 system for knocking out dmrt1 gene at double gRNA sites in yellow catfish and application

The invention discloses a CRISPR / Cas9 system for knocking out a dmrt1 gene at double gRNA sites in yellow catfish. The CRISPR / Cas9 system comprises the following steps: (1) designing a target site 1 on a first exon of the dmrt1 gene of the yellow catfish, and designing a target site 2 on a third exon; (2) designing a primer according to a target site sequence in the step (1) to detect the accuracyof the target sites in parent fishes, amplifying the target site 1 and nearby sequences by using dmrt1 E1 F and dmrt1 E1 R, and amplifying the target site 2 and nearby sequences by using dmrt1 E3 F and dmrt1 E3 R; (3) performing PCR amplification on a gRNA1 fragment by using dmrt1 E1 gRNA F and gRNA R by taking pUC19-gRNA-scaffold plasmid as a template, performing PCR amplification on a gRNA2 fragment by using dmrt1 E3 gRNA F and gRNA R, and performing in-vitro transcription and purification by taking the PCR product as a template to obtain gRNA; (4) performing in-vitro transcription synthesis on Cas9 mRNA by taking pXT7-hCas9 linearized plasmid as a template; (5) performing microinjection on the Cas9 mRNA and the two gRNAs into a cell-stage embryo of the yellow catfish; and (6) detectingthe mutation type, and calculating the gene editing rate.
Owner:SUN YAT SEN UNIV

Method for estimating breeding value by fitting genome with non-additive effect

The invention discloses a new method for estimating breeding value by fitting genome with non-additive effect. According to the method, an additive effect prediction model and a non-additive effect prediction model in genome selection are combined into a meta-algorithm of a prediction model,. Compared with a prediction model only fitting an additive effect, the method disclosed by the invention can generally obtain a better prediction effect. The method comprises the following specific steps of acquiring complete genotype information and phenotype information of a single group; randomly dividing a training group and a test group, and performing iterative training on the training group through a hybrid algorithm MixPGV; obtaining an expected additive effect value and an expected non-additive effect value of each SNP site, and performing accumulating to obtain an additive genome estimated breeding value GEBVAdd and a non-additive genome estimated breeding value GEBVNon-Add of an MixPGV prediction model; and accumulating the additive genome estimated breeding value GEBVAdd and the non-additive genome estimated breeding value GEBVNon-Add to obtain a genome estimated breeding value GEBVof the group, and finally calculating a correlation coefficient of the genome estimated breeding value GEBV and a real breeding value to obtain estimation accuracy.
Owner:JIMEI UNIV

Drug discovery method and device based on relationship extraction and knowledge reasoning and computer equipment

The invention relates to artificial intelligence, and discloses a drug discovery method and device based on relationship extraction and knowledge reasoning and computer equipment. The method comprisesthe steps of obtaining a relation type of a substance-gene entity pair and a gene-disease entity pair through a relation extraction model, and calculating a first possibility score of a substance targeting gene according to the relation type of the substance-gene entity pair; calculating a second likelihood score of the gene as a target gene of the disease according to the relationship type of the gene-disease entity pair; calculating a third likelihood score of the substance as a therapeutic substance for the disease. The relationship extraction model may be stored in a blockchain. Accordingto the method, substance-gene and gene-disease relationship types are automatically extracted from massive medical literatures, and knowledge is utilized to reasoning substances with treatment effects or potential treatment effects of the drugs, so that high cost and low recall of a scheme based on structural property similarity of the compounds are avoided, and more substances with potential curative effects can be obtained.
Owner:PING AN TECH (SHENZHEN) CO LTD

Dual-gRNA site amh gene knockout method in pelteobagrus fulvidraco and application

The invention discloses a dual-gRNA site amh gene knockout method in pelteobagrus fulvidraco. The method comprises the following steps of (1) designing a target site 1 on the first exon of a pelteobagrus fulvidraco amh gene, and designing a target site 2 on the fourth exon; (2) according to a target site point sequence design primer in the step (1), detecting the accuracy of the target site in parent fish, amplifying the target site 1 and a near sequence by using amh E1 F and amh E1 R, and amplifying the target site 2 and the near sequence by using amh E4 F and amh E4 R; (3) using a pUC19-gRNA-scaffold plasmid as a template, performing PCR amplification on a gRNA1 fragment by using amh E1 gRNA F and gRNA R, and performing PCR amplification on a gRNA2 fragment by using amh E4 gRNA F and gRNA R, wherein the PCR products are used as the template, in vitro transcription is performed, and purification is performed, so that gRNA is obtained; (4) using a pXT7-hCas9 linearization plasmid as atemplate, and performing in vitro transcription to synthetize Cas9 mRNA; (5) performing microinjection on Cas9 mRNA and two gRNA into a cell stage embryo of pelteobagrus fulvidraco; and (6) detectingthe mutation type, and calculating the gene editing rate. The invention further discloses an application of the method.
Owner:SUN YAT SEN UNIV

Method and system for predicting interaction between miRNA and gene based on multi-relational graph convolutional network

PendingCN114093422ARich forecasting meansFully capture the structureNeural architecturesSequence analysisInformation networksHeterogeneous network
The invention discloses a method and a system for predicting interaction between miRNA and a gene based on a multi-relational graph convolutional network. The method comprises: constructing a heterogeneous information network of miRNA and genes, and learning network topology features of nodes by using a multi-relational graph convolutional network based on the heterogeneous network; meanwhile, capturing effective characteristics of the gene sequence by using a recurrent neural network; and finally, combining network topology characteristics with sequence characteristics, and calculating an association prediction score of the miRNA-gene pair by using the obtained miRNA and gene embedding. According to the method, manual feature construction is not needed in the implementation process, representation learning is combined, the advantages of the multi-relation graph convolutional network are fully utilized, effective gene sequence information is mined, and feature representation of miRNA and gene nodes is better captured. Experimental results show that the MRMTI is superior to other comparison methods in the aspect of association prediction of miRNA and genes, and has good prediction performance.
Owner:HUNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products