9 results about "Gene pathway" patented technology

The invention provides a full-length gene sequence modeling method and system based on a neural network, and the method comprises the steps: constructing a first expression matrix for initial single-cell RNA sequencing data, and carrying out the quality control transformation of the first expression matrix to obtain a second expression matrix; inputting the second expression matrix into a preset binning embedding module to obtain a binning embedding matrix; maintaining and loading a gene pathway set through a knowledge base and a mapping module to obtain a binary mask matrix, and performing mask processing on the binning embedded matrix based on the binary mask matrix to obtain a pathway mask matrix; the path mask matrix is input into a preset attention state space model, the attention state space model comprises an encoder module, a jump connection module and a decoder module which are arranged in sequence, and a reconstruction tensor is output through the decoder module. According to the scheme, an efficient and extensible whole-gene annotation method is provided, and whole-gene expression input can be processed while the calculation efficiency is kept.

The invention discloses an application of a ClBZR1L gene in enhancing the cold resistance of watermelons by promoting proline accumulation. The invention belongs to the technical field of plant genetic engineering. The CDS sequence of the ClBZR1L gene is as shown in SEQ ID NO. 1. Experiments show that when a recombinant vector for constructing the silent ClBZR1L gene is transferred into a watermelon plant, the proline content of the silent plant under cold stress treatment is remarkably reduced compared with that of a control group, and the cold resistance is reduced. A recombinant vector for constructing the over-expression ClBZR1L gene is transferred into a watermelon plant, the proline accumulation amount of the over-expression plant under cold stress treatment is remarkably increased, the cold resistance is enhanced, and a gene resource is provided for watermelon cold-resistant molecular breeding. Besides, the invention also discloses direct combination of the ClBZR1L gene and a proline synthesis rate-limiting enzyme coding gene ClP5CS1 gene promoter, and the expression of the coding gene is up-regulated, so that synthesis of proline under cold stress is promoted, and a theoretical basis is provided for in-depth study on cold-resistant gene pathways.

The application provides a drug hepatotoxicity prediction method, device, system and medium, the method comprising: sequencing human liver cells after being contacted with a drug to be predicted to obtain a genome expression profile of the human liver cells after being contacted with the drug to be predicted; calculating the sum of the absolute values of the fold changes of the genes in the current gene pathway as the toxicity score of the current gene pathway according to the expression profile; calculating the Z value of the current gene pathway according to the toxicity score of the current gene pathway, the average value and the standard deviation value of the toxicity scores of the gene pathways calculated multiple times by a plurality of preset gene pathways; and predicting that the drug to be predicted has hepatotoxicity when the Z value is greater than 1.5. Therefore, the application can accurately, timely, effectively and sensitively predict drug hepatotoxicity without a large number of living animals as an experimental basis, and has good advantages in safety, environmental protection and animal protection. The application has the advantages of short experimental period and low cost.

The application relates to the technical field of biology, and provides a cell characterization model pre-training method, a cell downstream task processing method, equipment, a readable storage medium and a program product, which can improve cell characterization accuracy. The cell characterization model pre-training method comprises the following steps: determining a plurality of characteristic genes of a cell sample set, and obtaining a first characteristic gene sequence corresponding to each sample cell in the cell sample set; a plurality of gene pathways for realizing different biological functions are matched according to the plurality of characteristic genes; cell coding information corresponding to each sample cell is determined by a cell characterization model to be trained according to each first characteristic gene sequence and each gene pathway, a second characteristic gene sequence corresponding to each sample cell is predicted according to the cell coding information; the cell characterization model is adjusted according to the difference between the second characteristic gene sequence and the first characteristic gene sequence of the sample cell until a training end condition is met, and a pre-trained cell characterization model is obtained.

The application provides a single-cell RNA sequencing annotation method and device based on a dynamic hypergraph, relates to the technical field of bioinformatics, and comprises the following steps: obtaining a data set, extracting a low-dimensional embedding vector of each cell from a gene expression vector, and constructing a dynamic hypergraph with cells as nodes and gene pathways as hyperedges; extracting a pathway feature of each hyperedge from the dynamic hypergraph; calculating the importance weight of each cell in each hyperedge based on the low-dimensional embedding vector and the pathway feature of the hyperedge; inputting the dynamic hypergraph, the pathway feature and the importance weight into a preset hypergraph neural network for message aggregation and feature learning to generate a prediction label of a cell type; and training the hypergraph neural network through an optimization algorithm to obtain a trained cell annotation model. The application realizes more accurate and more biologically interpretable cell type and function annotation by introducing a hypergraph structure and a metabolic pathway activity dynamic modeling mechanism.

The present application relates to the technical field of biomedical detection, and particularly relates to an intelligent transcriptome analysis system based on a maternal-fetal interface biomarker. The system comprises a maternal-fetal RNA low-temperature storage module, a maternal-fetal genome sequencing calculation module, a transcriptome differential expression determination module and a transcription differential expression network construction module, can obtain a maternal-fetal interface biological blood sample set and perform RNA extraction and low-temperature storage to generate a maternal-fetal blood RNA low-temperature sample group; by constructing a maternal-fetal blood RNA sample library and performing single-end sequencing calculation and reference gene mapping screening, a maternal-fetal RNA reference genome is generated; based on the maternal-fetal RNA reference genome, differential expression genes are determined, target gene clustering and enrichment analysis are simultaneously performed, the gene pathway distribution corresponding to each gene classification is obtained, and gene expression network analysis is performed to generate a maternal-fetal target gene expression network. The present application can analyze the gene pathway network between maternal-fetal target genes.

This invention relates to a recombinant plasmid for preparing the natural sunscreen agents shinorine and porphyra-334 and its applications, belonging to the field of biotechnology. The recombinant plasmid contains *Gracilaria heteroclade*. Gh.mysAB Genes and heteroclade Gracilaria Gh.mysCD Genes; the aforementioned Gracilaria heteroclade Gh.mysAB The nucleotide sequence of the gene is shown in SEQ ID NO.1; the described *Gracilaria heteroclade* Gh.mysCD The nucleotide sequence of the gene is shown in SEQ ID NO.2. This invention utilizes a simplified two-enzyme catalytic system of Gracilaria heteroclade to replace the complex four-gene pathway of cyanobacteria, significantly improving catalytic efficiency; and overcomes the problem of seasonal shortage of natural resources, high energy consumption of pretreatment, and complex extraction process by heterologous expression in Saccharomyces cerevisiae, thereby reducing production costs and avoiding the risk of marine environmental pollution.

The application provides a cancer synergistically driven pathway identification system based on attribute heterogeneous network embedding, integrates mutation data, performs data alignment and preliminary screening, obtains gene weight, optimizes gene pathway relationship, constructs an attribute heterogeneous network, reconstructs a pathway interaction network, and defines the synergistically driven ability between pathways to determine the synergistically driven pathway. The application optimizes the relationship between gene pathways based on gene weight of the pathway structure, important genes can make greater contribution to the identification of the driven pathway, and reduces the interference of irrelevant genes on the result; the attribute heterogeneous network embedding is used to provide rich genetic information related to other biological molecules for pathway level analysis, and makes up for the insufficient / missing problem of biological information related to the pathway level; the defined synergistically driven ability between pathways comprehensively considers the high coverage, high mutual exclusivity, mutation co-occurrence and functional association of the synergistically driven pathway, and can efficiently and accurately identify the synergistically driven pathway.

This invention discloses an autism-assisted diagnostic method and system based on gene pathway mapping information, belonging to the interdisciplinary field of bioinformatics and machine learning. The invention first reads and preprocesses raw sequencing data to obtain a standardized differentially expressed gene matrix; then, it introduces pathway function and topological information to construct a pathway topological adjacency matrix, and obtains gene pathway features by dimensionality reduction, graph signal propagation, and feature encoding of the pathway feature matrix; subsequently, it performs initial training of a multimodal fusion network on the aforementioned two matrices; then, it selects Top K key genes based on gene importance scores and performs secondary training in conjunction with gene pathway features; finally, it inputs the gene expression levels of the subject to be tested and outputs the autism-assisted diagnostic classification results. By introducing gene pathway mapping as prior knowledge, this invention constructs a multimodal fusion network that combines biological interpretability and high robustness, which can improve the accuracy of autism diagnosis based on a small number of key features.