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57 results about "Computational gene" patented technology
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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.
A transcriptome annotation method and system based on a large language model
The present invention relates to the intersection of bioinformatics and computational biology, and discloses a transcriptome annotation method and system based on a large language model, including: fusing single-cell spatial coordinates and gene expression values into pseudo-image modal data, extracting spatial topological features of the pseudo-image modal data; performing cross-modal alignment between the spatial topological features and a preset medical database, and analyzing the cell type probability of the cross-modal embedding vector; constructing a functional semantic space of functional description texts, and projecting non-model species into the functional semantic space; calculating the semantic similarity between gene expression embeddings and homologous genes of reference species, and using a large language model to convert gene expression embeddings into semantic mapping relationships. The present invention reduces the core problems faced in single-cell spatial transcriptome annotation, such as extensive spatial topological modeling, low cross-modal alignment accuracy, limited non-model species annotation, and rigid semantic mapping.
Owner:INSTITUTE OF CROP SCIENCE CHINESE ACADEMY OF AGRICULTURAL SCIENCES +1
Method for evaluating cell population heterogeneity based on energy indexes
ActiveCN119252344Aaccurate identificationBiostatisticsRecognition of DNA microarray patternSingle cell transcriptomeCellular energy
The invention provides a method for evaluating cell population heterogeneity based on an energy index, and belongs to the technical field of biological recognition, and the method comprises the following steps: S1, preprocessing single cell transcriptome data; s2, carrying out feature selection on the preprocessed data, and defining a cell state; s3, constructing a gene local network based on a Hupfield neural network; s4, calculating gene local network energy and cell energy, and carrying out normalization processing on the cell energy; s5, introducing a Gaussian mixture model, identifying the potential state of the cells by analyzing the energy distribution difference of the cells, and clustering the cells in the same differentiation potential state; and step S6, evaluating the heterogeneity of the cell population. By adopting the method for evaluating the heterogeneity of the cell population based on the energy index, the complexity and the difference in the cell population can be disclosed more accurately.
Owner:INNER MONGOLIA UNIVERSITY
GEP-GANGP-based genome prediction system and method
The invention relates to the field of genome prediction, and particularly discloses a GEP-GANGP-based genome prediction system and method, and the method comprises the steps: generating synthetic phenotype data by using GEP-cGAN; processing real and synthetic data through a feature extraction network; calculating interaction characteristics of the genotype and the environment by adopting a cross-modal attention mechanism; a transfer learning module is used for realizing knowledge transfer and feature enhancement; synchronously outputting a phenotype prediction value, an effect weight and an interpretability characteristic through a multi-task decoder; the system comprises a GEP-cGAN module, a biological multi-head attention mechanism BMAM module, a cross-modal interaction feature extraction module, a transfer learning TrG2P module and a multi-task decoder module. According to the method, the problems of low prediction precision, poor generalization ability and weak model interpretability in a small sample scene in forest tree breeding are solved, the accuracy and practicability of genome prediction are remarkably improved, and reliable technical support is provided for forest tree genetic improvement.
Owner:RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
Data analysis system and method of gene regulation and control network based on deep regression algorithm
ActiveCN119252332AOvercome the shortcomings in personalized treatmentImprove noise immunityBiostatisticsHybridisationAlgorithmData analysis system
The invention is suitable for the technical field of data analysis, and provides a data analysis system and method of a gene regulation and control network based on a deep regression algorithm, and the method comprises the following steps: converting gene identity and gene expression quantity values into vector representation; calculating an attention score between gene vector representations as an evaluation criterion of a relationship between genes; and predicting the specific gene expression quantity. By introducing the Gaussian layer, the anti-noise performance is enhanced, embedding and attention mechanisms are utilized, the complex regulation and control relation between genes is captured, individualized GRN prediction is achieved on the single cell level, the defects of an existing method in individualized treatment of cancer patients can be overcome, and the method has a good application prospect. And the gene expression quantity analysis and prediction in individual treatment of cancer patients are supported.
Owner:JILIN UNIVERSITY
A single-cell trajectory inference method based on adaptive feature selection
This invention belongs to the field of bioinformatics and relates to a single-cell trajectory inference method based on adaptive feature selection. First, an initial gene expression matrix is obtained through data preprocessing and screening for highly variable genes. Second, a two-dimensional evaluation strategy is employed to calculate the scores of highly variable genes with gene expression variability and the trajectory importance score related to differentiation trajectories. Then, a dynamic weight fusion mechanism is introduced, adaptively adjusting the fusion weights of the two scores based on performance feedback, and highlighting key genes through nonlinear enhancement. Next, an intelligent inflection point detection algorithm adaptively determines the optimal number of features. Finally, trajectory inference is performed based on a variational autoencoder model reconstructed from feature subsets, and a performance-driven feature selection closed loop is formed through multiple rounds of iterative optimization. This invention achieves high-precision, adaptive single-cell trajectory inference, solving the technical problems of single feature selection and fixed weights in traditional methods.
Owner:LUDONG UNIVERSITY
A gene regulation relationship prediction method based on matrix enhancement and feature fusion
The application discloses a gene regulation relationship prediction method based on matrix enhancement and feature fusion, and comprises the following steps: 1, obtaining N genes G and their regulation relationship R; 2, calculating the directed adjacency matrix of the genes according to R; 3, generating the similarity matrix of the source genes and normalizing the similarity matrix; 4, generating the similarity matrix of the target genes and normalizing the similarity matrix; 5, processing the normalized source gene similarity matrix and the normalized target gene similarity matrix respectively by adopting an EASNN method, and performing matrix enhancement processing on the adjacency matrix; 6, generating the covariance matrix Co of the genes, and selecting the neighborhood gene pair set of any gene pair according to Co; 7, obtaining the total histogram set Mg of each gene pair according to G; 8, obtaining the total enhanced histogram set Ma of each gene pair; and 9, constructing a CNN network to obtain the probability that a regulation relationship exists between each gene pair. The application can effectively fuse the gene expression features and the enhanced network structure features, so that the regulation relationship between the genes can be more accurately predicted.
Owner:ANHUI UNIV
Drug analysis and repurposing platform with synergy and disease clustering capabilities
A method for maintaining a gene description dataset associated with a plurality of genes with respect to a given disease, wherein the gene description dataset is a human- comprehensible text-based dataset generated by a Large Language Model (LLM); maintaining a dataset of drug mechanisms of action (MOAs) associated with a plurality of drugs; embedding the gene descriptions and the MOAs into high-dimensional vectors using a text embedding technique to generate gene description vectors and MOA vectors; calculating distances between the gene description vectors and the MOA vectors to generate distance scores; and ranking the drugs for the given disease based on an aggregated distance score between the MOA vectors and the vectors of genes associated with the given disease.
Owner:BIOSSIL INC
Method for predicting and screening two-to-two interaction of lactobacillus bulgaricus and streptococcus thermophilus
The invention provides a two-to-two interaction prediction and screening method for lactobacillus bulgaricus and streptococcus thermophilus, and belongs to the technical field of food production. The method comprises the following steps: calculating whole genome k-mer data of two strains of lactobacillus bulgaricus and two strains of streptococcus thermophilus to form respective feature vectors, and calculating a gene copy number to construct a KEGG matrix; and generating a comprehensive feature vector by combining the KEGG feature frequency and the k-mer feature frequency. The first 200 important features are screened out from a real label sample by utilizing chi-square test, gradient lifting and variance analysis. And then, generating a pseudo-label sample through a generative adversarial network (GAN), and constructing a machine learning model in combination with a real label sample for predicting the interaction effect of the strain combination. And finally, verifying the accuracy of model prediction through a fermentation test, and selecting an optimal model. According to the method, the interaction symbiotic potential of the strain combination can be efficiently predicted, and the yoghurt production efficiency and quality are improved.
Owner:INNER MONGOLIA AGRICULTURAL UNIVERSITY
Method and system for mapping read sequences using a pangenome reference
There is a demand for low-cost efficient robust method for mapping read sequences with genome variation graph in genomic study. This disclosure herein relates to a method and system for mapping read sequences with genome variation graph by constructing a subgraph using a novel combination of graph embedding and graph winnowing techniques. The system processes the obtained plurality of read sequences and a genome variation graph for constructing the subgraph by computing an embedding for the genome variation graph utilizing a graph embedding technique. Further, graph index is generated for the genome variation graph based on the embedding and the genome variation graph utilizing the graph winnowing technique. Then computes gapped alignment score for read sequence (r) with its corresponding subgraph. Thus, enables a reliable method for read sequence with accurate, memory efficient and scalable system for mapping read sequences with genome variation graph.
Owner:TATA CONSULTANCY SERVICES LTD
Method and computer system for analyzing single-cell transcriptome data pseudo-time trajectories
The application discloses a single-cell transcriptome data pseudo-time trajectory analysis method and a computer system, which comprises the following steps: 1) calculating a gene explicit comparison advantage matrix; 2) obtaining a gene similarity matrix by similarity and constructing a gene network; 3) taking an initial node in the gene network, starting random walking from the initial node, recording each gene walked through to form a gene text composed of gene sequences; 4) converting the gene text into a gene word vector; 5) adding all single-cell expressed gene vectors with expression as weight to form a sum vector as a word vector representation of the single cell in the gene space; and 6) visualizing all cell vector representations to obtain an embryo cell development pseudo-time trajectory result. The application provides an analysis basis for identifying different rare cell subtypes in tissues and variant genes of different cell subtypes and has a wide and important application prospect in the fields of tumors, developmental biology and life science.
Owner:WENZHOU INST UNIV OF CHINESE ACAD OF SCI
Analysis method for HBV expression level and fragment distribution based on single-cell RNA-seq
The invention relates to the technical field of biological industry, and discloses a single-cell RNA-seq-based HBV expression level and fragment distribution analysis method, which comprises the following steps: constructing position information of each HBV gene in a linear transcriptome and a circular genome to obtain a mapping relationship between the transcriptome and the genome; sequencing original data obtained by scRNAseq is compared to an HBV transcriptome reference sequence, and a human source sequence and an HBV source sequence are recognized; removing a human source sequence to obtain an HBV source transcriptome sequence; converting the position of the HBV source transcriptome sequence aligned on the transcriptome into an alignment position on the genome according to the mapping relation between the transcriptome and the genome; and calculating the number of the sequencing sequences covered on each basic group of the genome, and drawing the coverage depth of each basic group of the HBV genome to obtain the expression level and fragment distribution of the single-cell RNA-seq sequencing data on the HBV genome. The blank of the HBV analysis method based on the single cell resolution is filled.
Owner:WEST CHINA HOSPITAL SICHUAN UNIV
Disease gene identification method and system based on heterogeneous network pulse dynamics
InactiveCN119649913Aimprove performanceImprove predictive performanceData visualisationBiostatisticsTheoretical computer scienceGene identifier
The invention discloses a disease gene identification method and system based on heterogeneous network pulse dynamics, and the method comprises the following steps: obtaining a GGA (Gene Associated Network), a DDA (Disease Associated Network) and a DGA (Disease Gene Associated Network), function similarity scores between gene nodes and function similarity scores between disease nodes are respectively calculated through a GGA network, a DDA network and a DGA network to enhance the GGA network and the DDA network, the enhanced GGA network and the enhanced DDA network are both combined with the DGA network, and an enhanced double-layer heterogeneous network comprising a disease layer and a gene layer is constructed; applying a pulse signal to an excitation node of the enhanced double-layer heterogeneous network, and tracking by taking a dynamic response of a node to be predicted to pulse excitation as a function of time to obtain a heterogeneous network dynamic pulse model; and according to the enhanced heterogeneous network dynamic pulse model, acquiring the maximum pulse response of the node as an effective pulse dynamic feature to identify a disease gene.
Owner:CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
LAMA5 expression-based pan cancer prognosis evaluation system
A generic cancer prognosis evaluation system based on LAMA5 expression provided by the invention relates to the technical field of generic cancer prognosis evaluation, and comprises the following steps: acquiring multi-source molecular data, establishing a standardized data input path to obtain LAMA5 gene molecular information, and completing sample identification and field standardization by calculating mutation frequency and gene copy number variation of the LAMA5 gene molecular information to obtain a generic cancer prognosis evaluation result. And an LAMA5 generic cancer molecular database is formed. A standardized data input path and a unified field format are formed by establishing an LAMA5 generic cancer molecular database and integrating TCGA, GTEx, a human protein map and other multi-source molecular data, the database achieves generic cancer prognosis evaluation system calculation of LAMA5 mutation frequency and gene copy number variation, the data consistency and statistical reliability of multiple cancer species are improved, and the method is suitable for large-scale popularization and application. And a data basis is provided for pan-cancer level expression and variation analysis.
Owner:NINGXIA HUI AUTONOMOUS REGION PEOPLES HOSPITAL
High-specificity gene / site combination screening method based on Bayesian optimization
The invention discloses a gene / site combination screening method based on Bayesian optimization, a gene / site combination with the highest sample type specificity is screened by using a Gaussian process model, the kernel function of the Gaussian process model is a two-factor vertical cross-linked kernel, and comprises two cores of basic variation and discrete variation; on the basis of differences in the same sample type, the dispersion degree between different sample types is used as an auxiliary item, and the relation between two gene / site combinations is calculated. According to the method disclosed by the invention, the correlation of each gene / site in different gene / site combinations in the same sample type and in different sample types can be evaluated, and the gene / site characteristics required in biology are fully fused into the gene / site screening process; the high efficiency, specificity and accuracy of computational gene / site screening are remarkably improved, and meanwhile the upper limit of the number of gene / site screening is remarkably increased.
Owner:SUZHOU HAIMIAO BIOTECH CO LTD
Method for analyzing and mining key genes for regulating and controlling non-structural carbohydrate distribution of emmenopterys henryi under shading condition based on weighted gene co-expression network
The invention relates to a method for analyzing and excavating key genes for regulating and controlling non-structural carbohydrate distribution of emmenopterys henryi under a shading condition based on a weighted gene co-expression network. The method comprises the following steps: S1, obtaining root, stem and leaf samples of emmenopterys henryi under different illumination conditions; s2, non-structural carbon index determination and transcriptome sequencing; s3, establishing a weighted gene co-expression network model, and dividing the weighted gene co-expression network model into a plurality of gene modules; calculating the correlation between the feature gene of the gene module and a non-structural carbon index, and screening a key gene module; and performing gene connectivity calculation and gene function annotation on the key gene module, and screening key genes. The 19 key candidate genes participating in regulation and control of the non-structural carbon distribution of the emmenopterys henryi under the shading condition are successfully excavated and identified, a foundation is laid for further clarification of a molecular mechanism of highlight stress response of the emmenopterys henryi, theoretical support is provided for development of an effective emmenopterys henryi conservation technology and promotion of emmenopterys henryi population recovery, and the important significance is achieved.
Owner:SHANGHAI INST OF TECH
Nitrogen cycle function gene prediction method and system based on multi-feature fusion
The invention belongs to the technical field of information prediction, and provides a nitrogen cycle function gene prediction method and system based on multi-feature fusion, and the method comprises the steps: obtaining protein sequence data of a nitrogen metabolism gene; analyzing the protein sequence data, screening out protein sequence data with class imbalance, performing protein sequence data enhancement based on a pseudo mutation strategy, and forming a balanced protein sequence data set by a minority of class protein sequences after data enhancement and protein sequences without class imbalance; balanced protein sequence data sets with different lengths are processed based on a bidirectional long-short-term memory network, context features of amino acid residues are extracted, and a relationship between any two amino acid residues is constructed through a self-attention mechanism to extract global features of the amino acid residues in the protein sequence. The context features and the global features are fused through a deep neural network, the prediction probability of the gene family is calculated based on the fused features, and the nitrogen cycle function genes are predicted.
Owner:UNIV OF JINAN
A method and system for endometriosis subtyping
The application relates to an endometriosis subtype identification method and system, relates to the fields of bioinformatics and medical diagnosis auxiliary technologies, and takes transcriptome expression data as input, constructs a standardized expression matrix, and adopts consistency clustering to perform subtype modeling to obtain a molecular subtype label; expression timing structure of a menstrual cycle phase is introduced to perform dynamic gene identification and discriminant power evaluation, and immune cell infiltration inference and path activity scoring are combined to analyze differences of the subtypes in an immune and inflammation network, then gene-pathway / gene-cell correlation is calculated to form multi-dimensional typing information with mechanism orientation. Based on the above results, an interpretable typing identification model is constructed, which provides a new technical means for accurate diagnosis and target identification of endometriosis.
Owner:FOSHAN MATERNAL & CHILD HEALTH CARE HOSPITAL
Detection of a genomic sequence in a microorganism genome by whole genome sequencing
PendingUS20250218539A1BiostatisticsDesign optimisation/simulationMicroorganismWhole genome sequencing
A method for detecting target genomic sequences at predetermined positions in a sequenced genome of a microbial organism in the form of reads. The method comprises computing a local sequencing depth of the genome in a neighborhood of the position of a target genomic sequence, the computing including a) detecting in the reads a set of digital genomic sequences from at least one reference genome of the microbial organism, b) generating of third set of digital genomic sequences comprising reads and digital genomic sequences of the second set belonging to the neighborhood c) counting the number of copies of each digital genomic sequences of the third set of digital genomic sequences, and d) computing the local sequencing depth as being equal to the maximum of the counted numbers of copies.
Owner:BIOMERIEUX SA
Method for detecting egg components in food, kit and application
PendingCN121249860AMicrobiological testing/measurementDNA/RNA fragmentationBiotechnologyEggs per gram
The invention discloses a method for detecting egg components in food, a kit and application wherein the method comprises the following steps: step 1, crushing or homogenizing the food to be detected, and extracting DNA by using a DNA extraction kit; step 2, a microfluidic digital PCR amplification system is adopted, a primer pair and a probe of the targeted chicken mitochondrial gene ND1 are used for amplification reaction, and reaction parameters are set as follows: the annealing temperature is 56-60 DEG C, the final concentration of the primer is 500-800 nmo l / L, and the final concentration of the probe is 100-400 nmo l / L; and step 3, analyzing and calculating the copy number of the ND1 gene through a micropore fluorescence signal. The invention aims to improve the sensitivity of the method for detecting egg components in food.
Owner:CHANGSHA FOOD & DRUG INSPECTION INST
An analysis method for hbv expression level and fragment distribution based on single cell rna-seq
The application relates to the technical field of biological industry, and discloses an analysis method for HBV expression level and fragment distribution based on single-cell RNA-seq, constructs position information of each gene of HBV in a linear transcriptome and a circular genome, and obtains a mapping relationship of the transcriptome and the genome; compares original sequencing data obtained by scRNA-seq to an HBV transcriptome reference sequence, identifies human sequences and HBV sequences, removes the human sequences, and obtains HBV source transcriptome sequences; converts the position of the sequencing sequence on the transcriptome into a comparison position on the genome through the mapping relationship of the transcriptome and the genome; calculates the number of sequencing sequences covered on each base of the genome, draws the coverage depth of each base of the HBV genome, and obtains the expression level and fragment distribution of single-cell RNA-seq sequencing data on the HBV genome. The application fills the blank of the HBV analysis method based on single-cell resolution.
Owner:WEST CHINA HOSPITAL SICHUAN UNIV
Function generalization and attractor determination method for gene regulatory network
The invention provides a function generalization and attractor determination method for a gene regulatory network, which comprises the following steps: for each target gene in the gene regulatory network, calculating a Cramer correlation coefficient between the target gene and all regulatory genes corresponding to the target gene, and selecting the regulatory gene with the highest Cramer correlation coefficient value as guidance; setting other unobserved values in the truth table of the gene regulation and control network; and based on a gene regulatory network truth table, obtaining attractors by traversing each state of the gene. According to the method, the correlation between the genes is calculated by adopting the Cramer correlation coefficient, the problem of low accuracy of the existing algorithm is effectively improved, and the algorithm using the Cramer correlation coefficient and the algorithm proposed in the prior art are subjected to a large amount of experimental comparison; it is proved that the average sensitivity error and the steady-state distribution distance of the method are both reduced, and therefore the effect that truth table prediction is more accurate is achieved.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Cell fate mapping research method based on CytoEnry technology
The invention provides a cell fate mapping research method based on a CytoEnry technology, and belongs to the technical field of biological recognition, and the method comprises the following steps: S1, preprocessing single cell transcriptome data; s2, constructing a gene local network based on a Hupfield neural network; s3, calculating gene local network energy and cell energy, and carrying out normalization processing on the cell energy; s4, introducing a Gaussian mixture model, identifying the potential state of the cells by analyzing the energy distribution difference of the cells, and clustering the cells in the same differentiation potential state; s5, identifying cells in different fate end states; and step S6, deducing a cell lineage trajectory. According to the method, under the condition of not depending on prior knowledge, the technology provides direction information for deducing cell fate transformation from the beginning from the perspective of cell plasticity, and the dynamic change process of the cell fate can be accurately recovered.
Owner:INNER MONGOLIA UNIVERSITY
Method for rapidly identifying plant imprinting gene based on multi-species sequence conservative property
The invention relates to the cross technical field of bioinformatics and epigenetics, and particularly discloses a method for rapidly identifying plant imprinting genes based on multi-species sequence conservation.The method comprises the steps that a whole genome gene set of target plant species is obtained; selecting reference plant species with different genetic relationships with the target plant species, obtaining an optimal homologous gene of each gene of the target plant species in the reference plant species, and constructing a multi-species homologous sequence set; performing multi-sequence comparison on the multi-species homologous sequence set, and calculating a conservative score of each target gene based on a comparison result; and sorting and screening the target genes based on the conservative scores, and preliminarily identifying the genes with the conservative scores higher than a set threshold as candidate plant imprinting genes. According to the method, high-throughput and low-cost screening and prediction of potential plant imprinting genes are realized by utilizing the characteristic that the plant imprinting genes have higher conservative property in an evolution process and calculating cross-species conservative property scores of the genes.
Owner:YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
MICP functional gene regulation network analysis method, device, equipment and medium
The invention relates to the technical field of bioinformatics, and discloses an MICP functional gene regulatory network analysis method, device and equipment and a medium. Expression data of an MICP functional gene is binarized and mapped into a one-dimensional ordered sequence; secondly, coding the gene state sequence into a quantum state vector, and performing efficient compression expression on the quantum state vector by using a matrix product state tensor network; on this basis, quantum mutual information between the gene pairs is calculated to construct a binary regulation skeleton network, and multi-element quantum mutual information is further calculated to identify a significant multi-gene synergy or redundancy regulation module; and finally, screening a reliable relationship through statistical test, integrating and constructing a comprehensive regulation and control network, performing function analysis, breaking through the bottleneck of a traditional method on high-order relationship capture through quantization and a tensor network, and remarkably improving the robustness and analysis depth of network inference.
Owner:LONGYAN UNIV
A gene expression profile classification method and system based on feature dependency and multi-objective particle swarm optimization feature selection
ActiveCN119889460BInternal combustion piston enginesBiostatisticsClassification methodsFeature dependency
The application provides a gene expression profile classification method and system based on feature dependence and multi-objective particle swarm optimization feature selection, comprising the following steps: calculating the dependence score of each feature of the gene expression profile data, quantifying the dependence relationship between features by information entropy and mutual information; initializing the particle swarm based on the dependence score, and preferentially selecting features with high dependence scores; adopting a multi-objective particle swarm optimization algorithm for feature selection, combining the classification error rate and the feature selection rate as the objective function, and realizing the balance between low error rate and feature subset selection in the optimization process; adopting an improved particle optimal position updating strategy, generating new solutions through a non-dominated solution updating mechanism based on cubic spline interpolation, and improving the global search ability of the particle swarm; and obtaining the optimal feature subset through the multi-objective optimization process. Through the optimization of the feature selection process and the improvement of the particle swarm optimization strategy, the application improves the classification performance and the efficiency of feature selection, and can effectively capture the dependence relationship between genes.
Owner:JIANGSU UNIV
A method, device and medium for analyzing a MICP functional gene regulation network
The present application relates to the technical field of bioinformatics, and discloses a MICP functional gene regulation network analysis method, device, equipment and medium. The expression data of the MICP functional gene is binarized and mapped into a one-dimensional ordered sequence. Secondly, the gene state sequence is encoded into a quantum state vector, and a matrix product state tensor network is used for efficient compression representation. On this basis, not only the quantum mutual information between the genes is calculated to construct a binary regulation skeleton network, but also the multi-element quantum mutual information is further calculated to identify significant multi-gene synergistic or redundant regulation modules. Finally, reliable relationships are screened through statistical tests, and a comprehensive regulation network is integrated and constructed for function analysis. Through quantumization and tensor network, the bottleneck of traditional methods in high-order relationship capture is broken through, and the robustness and analysis depth of network inference are significantly improved.
Owner:LONGYAN UNIV
Method for constructing genome selective breeding technology system of villus sheep
The invention provides a method for constructing a genome selective breeding technical system of downy sheep, and relates to the technical field of genome selective breeding of downy sheep, the method comprises the following steps: constructing a reference group, selecting samples from downy sheep with multiple regions and multiple genetic backgrounds, collecting phenotypic data, and carrying out genetic typing; then establishing a genome selection model, processing genotype and phenotype data, and training by using GBLUP and Bayesian models; then, candidate groups are screened, a genome estimation breeding value is calculated, and individuals ranked in the first 20%-30% are selected; a breeding scheme is formulated, breeding is carried out without too large inbreeding coefficient, and progenies are determined and analyzed; and finally, collecting new data every year, and retraining the model every 2-3 years. Regional ecological differences of a reference group, a model algorithm, a convergence threshold value and candidate group phenotype evaluation index weights are limited, and the breeding effect of the villus sheep can be optimized.
Owner:XINJIANG ACAD OF ANIMAL SCI
Differential gene identification method based on non-parametric test
The application discloses a differential gene identification method based on non-parametric test. Gene expression matrices of an experimental group and a control group are obtained. An MMD unbiased empirical estimation between gene expression level sequences of genes in the experimental group and gene expression level sequences of the genes in the control group is calculated as an original MMD unbiased empirical estimation of the genes. Gene expression levels in the gene expression level sequences of the genes in the experimental group and the control group are combined and then randomly shuffled and rearranged, and an MMD unbiased empirical estimation is calculated as a new MMD unbiased empirical estimation. The significance parameter of the genes is calculated, and the differentially expressed genes are determined according to the significance parameter. The method does not depend on specific data distribution assumptions, can more flexibly process data sets with few time points or large gene expression level fluctuations, is suitable for various types of gene expression data, and improves the flexibility and applicability of analysis.
Owner:WUHAN BOTANICAL GARDEN CHINESE ACAD OF SCI
Box separation method and device of metagenome assembly sequence, electronic equipment and storage medium
The invention provides a binning method and device for metagenome assembly sequences, electronic equipment and a storage medium, and the method comprises the following steps: obtaining common tag sequencing data of a preset microbial community and a genome assembly sequence set, the co-tag sequencing data comprises a plurality of gene segments corresponding to the preset microbial community and tag data corresponding to each gene segment; performing sequence comparison on the common-tag sequencing data and each genome assembly sequence in the genome assembly sequence set to obtain a tag sequence set corresponding to each genome assembly sequence in the genome assembly sequence set; calculating a first correlation degree between the genome assembly sequences in the genome assembly sequence set according to the tag sequence set corresponding to each genome assembly sequence; and performing binning on the genome packaging sequences in the genome packaging sequence set based on the first correlation degree to obtain a binning result. According to the embodiment of the invention, the box separation fineness and accuracy can be improved. The embodiment of the invention can be applied to the fields of metagenomics and the like.
Owner:SHENZHEN HUADA GENE INST +1
Cardiovascular state-oriented circadian rhythm assessment method and system
The invention provides a circadian rhythm evaluation method and system oriented to cardiovascular states, and belongs to the field of transcriptional gene analysis, and the method comprises the steps: obtaining transcriptome data at a single time point; gene expression data are positioned and extracted from the transcriptome data through a preset rhythm homeostasis gene module, and the rhythm homeostasis gene module is constructed through a weighted gene co-expression network analysis algorithm; and calculating the collaboration, the volatility and the network concentration degree of the gene expression data based on a dynamic network biomarker algorithm, and determining the circadian rhythm disorder index of the to-be-evaluated user according to the collaboration, the volatility and the network concentration degree. According to the method, collaborative expression characteristics are systematically captured by using a rhythm homeostasis gene module, dependence on a small number of core clock gene signals is avoided, and quantitative calculation is carried out on the collaboration, volatility and network concentration ratio of gene expression data in the module based on a dynamic network biomarker algorithm; and an objective and quantifiable molecular evaluation index is provided for an individual rhythm state.
Owner:ZHENGZHOU UNIV