1211 results about "Expression gene" patented technology

The invention provides an UTR element NHP1 as well as a construction method and application thereof, and relates to the technical field of mRNA. A 5 'UTR with a good expression effect is designed by integrating dominant sequences of a human high-expression gene and a pathogen natural UTR, a chimeric structure NHP1 with high ribosome load is predicted through a calculation model, a DNA sequence of the NHP1 is as shown in SEQ NO 1, and an RNA sequence of the NHP1 is as shown in SEQ NO 2; an EGFP report system is adopted on the DNA level to rapidly screen UTR; the translation efficiency is quantitatively evaluated on the RNA level through luciferase mRNA (N1-methyl pseudouridine modification); and the particle size is controlled by a microfluidic technology, so that the optimized UTR-mRNA is efficiently expressed after being delivered.

The invention belongs to the technical field of plant genetic engineering, and particularly relates to an SCRE10 gene for improving rice disease resistance and application of the SCRE10 gene, the base sequence of the SCRE10 gene is shown as SEQ ID NO.1, and the amino acid sequence of the SCRE10 gene is shown as SEQ ID NO.2. Through construction of a dexamethasone induced expression SCRE10 transgenic rice plant, it is found that the transgenic rice can significantly induce PR gene expression and active oxygen outbreak, and the resistance of rice to false smut and bacterial leaf blight can be improved. The invention proves that heterologous inducible expression of the Ustilaginoidea virens SCRE10 gene has the function of positively regulating the disease resistance of the rice, and the SCRE10 gene can be used for improving the disease resistance of the rice, which is of great significance to the creation of disease-resistant germplasm of the rice.

The present disclosure relates to compositions and methods for reducing expression of MYC gene in a cell. In some embodiments, an expression repressor comprises a targeting moiety that binds a MYC promoter, anchor sequence, or super-enhancer. In some embodiments, the expression repressor comprises an effector moiety that represses transcription or methylates DNA. Systems comprising two expression repressors are also disclosed. The compositions can be used, for example, to treat cancers such as HCC.

Methods and systems for performing a clinical prediction are provided. In one example, the method comprises: receiving first molecular data of a patient, the first molecular data including at least gene expressions of the patient; receiving first biopsy image data of the patient; processing, using a machine learning model, the first molecular data and the first biopsy image data to perform a clinical prediction of the patient's response to a treatment, wherein the machine learning model is generated or updated based on second molecular data including at least gene expressions and second biopsy image data of a plurality of patients; and generating an output of the clinical prediction.

The invention discloses a breast cancer lymph node metastasis prediction system based on a gene spectrum, and relates to the technical field of breast cancer prediction systems. Comprising a data acquisition module which collects gene spectrum data of a breast cancer patient and collects detailed clinical information of the patient; the preprocessing module is used for carrying out data cleaning and data normalization processing on the collected data; and the feature extraction module is used for extracting principal component features by applying principal component analysis on the basis of the gene expression data. According to the method, gene expression data are considered, various gene spectrum data such as gene mutation and copy number variation and detailed clinical information are integrated, the biological characteristics of the breast cancer can be reflected more comprehensively, and the prediction accuracy is improved.

The invention belongs to the technical field of plant genetic engineering molecular breeding, and particularly relates to application of wheat TabHLH93 protein or a coding gene thereof in regulation and control of plant grain development. According to the invention, a binary expression vector capable of realizing ectopic expression of the TabHLH93 gene is constructed and is genetically transformed into common wheat to obtain a progeny with high expression of the TabHLH93 gene, so that overexpression of the TabHLH93 gene is realized, and it is verified that the TabHLH93 has a function of regulating and controlling the size of wheat grains and also has an important regulation and control effect on agronomic characters such as wheat plant height, tiller number, spike length and thousand seed weight. A candidate gene with an important application prospect is provided for wheat high-yield genetic improvement, and the gene has important significance for guaranteeing grain safety.

The invention discloses a SbWRKY51 gene, a promoter and application of the SbWRKY51 gene and the promoter in improvement of salt tolerance of sorghum, and belongs to the technical field of plant genetic engineering. The SbWRKY51 gene is screened from sorghum, and the expression level of the SbWRKY51 gene is up-regulated after salt stress treatment. The protein coded by the gene belongs to a WRKY transcription factor family, has transcriptional activation activity, and can start the expression of a reporter gene. Sorghum overexpression strains and complementary strains of the gene are obtained, salt tolerance related physiological indexes are measured, overexpression of the gene can improve the seed germination rate, increase the seed root length, regulate ion balance and enhance the free radical scavenging capacity of plants, and the effect of the gene in the aspect of improving the salt tolerance is embodied. A further research finds that the SbWRKY51 gene can enhance the plant salt tolerance by regulating a lignin synthesis pathway. The technical scheme provides a basis for cultivating resistant plants, and has important guiding significance for enhancing the production potential of sorghum under a high-salt condition and promoting agricultural development.

The invention discloses a breast cancer recurrence risk prediction method and system based on multi-modal data missing interpolation and gene interpretability enhancement. The method comprises the following steps: firstly, dynamically generating and complementing features of a missing mode by matching a generative adversarial network with a mode missing mask matrix; then, a feature screening mechanism driven by gene information is introduced, through a multi-task learning network, image feature extraction is supervised by using a gene expression tag in a model training process, and image features highly associated with recurrence-related genes are screened out; and finally, fusing the complemented multi-modal time sequence characteristics by adopting Transform, and outputting a recurrence risk probability. According to the method, the robust prediction performance can be realized under the condition of data missing, and meanwhile, image interpretation with a molecular biology basis is provided for the feature screening process of the model, so that the reliability and clinical acceptability of the whole system are enhanced.

The invention belongs to the technical field of molecular biology, and particularly relates to a CeNF-YA3 gene, an expression vector and application of the CeNF-YA3 gene in vegetable fat regulation and control. The nucleotide sequence of the CeNF-YA3 gene is as shown in SEQ ID NO.1. After the CeNF-YA3 gene is over-expressed, the grease content of arabidopsis seeds and leaves can be remarkably increased; in addition, the invention also provides a series of vectors containing the CeNF-YA3 gene for subcellular localization, yeast hybridization and plant overexpression for the first time, and proves that the CeNF-YA3 protein has a transcriptional activation function, is localized in a cell nucleus and accords with the basic characteristics of transcription factors for the first time. Therefore, the technical scheme of the invention provides scientific guidance for the application of the CeNF-YA3 gene and the protein thereof.

The invention discloses a drug perturbation diffusion prediction method fused with cell description, and relates to the technical field of drug perturbation prediction.The method comprises the steps that firstly, a cell perturbation transcriptome database is preprocessed, and a cell-drug combination containing drug characteristics, cell line gene expression and cell line description characteristics is obtained to serve as training data; and then constructing a drug disturbance prediction diffusion model based on cell description, training the drug disturbance prediction diffusion model by using the training data, and finally inputting Gaussian white noise, cell line gene expression before disturbance, drug characteristics and cell line description characteristics into the trained model to predict cell line gene expression after drug disturbance. According to the method, cell line description characteristics are introduced, so that the perception capability of the model on intercellular biological differences is enhanced, and the generalization performance of cross-drug and cross-cell lines is improved.

The invention discloses application of an apple MdMYS1 gene in regulating and controlling the wax content of plant fruits and leaves, and belongs to the technical field of plant genetic engineering. According to the invention, the MdMYS1 gene with high expression quantity in apple varieties with more waxiness is separated, and the nucleotide sequence of the MdMYS1 gene is shown as SEQ ID NO. 1. Through subcellular localization, the transcription factor expressed by the MdMYS1 gene is found to be localized on a cell nucleus. Experimental results show that overexpression of the MdMYS1 gene can significantly increase the wax content of the apple fruits and leaves by promoting biosynthesis of wax, which indicates that the MdMYS1 gene plays a key role in regulation and control of the wax content of the apple fruits and leaves. The invention provides an efficient and rapid way for apple breeding, provides a gene material for improving apple quality, and has a wide application prospect in improving economic benefits and ecological benefits of apple planting.

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 a grain specific promoter in the early stage of rice filling and application thereof, the promoter is named as proASP1, and the nucleotide sequence of the promoter is shown as SEQ ID NO: 1. The promoter has highly strict spatio-temporal expression specificity, the activation expression of the promoter is only limited in grains in the early stage of rice filling (4-12 days after flowering), especially the expression of genes is efficiently driven in endosperm and aleurone layers, and the expression is not leaked in other tissues such as roots, stems, leaves, leaf sheaths and glumes and grains in the middle and later stages of filling. The invention provides a basic and precious molecular tool for gene function research, quality improvement (such as protein and starch synthesis regulation) and bioreactor development in a key window period of rice grain development, and has important scientific research and application values.

The invention belongs to the technical field of molecular biology, and particularly relates to a CeNF-YA1 gene, an expression vector and application of the CeNF-YA1 gene in vegetable fat regulation and control. The invention provides the CeNF-YA1 gene for the first time, the nucleotide sequence of the CeNF-YA1 gene is as shown in SEQ ID NO.1, the full length of a coding region of the CeNF-YA1 gene is 792 bp, a series of carriers containing the CeNF-YA1 gene, such as subcellular localization, yeast hybridization and plant overexpression, are constructed for the first time, and meanwhile, the CeNF-YA1 protein is proved to have a transcription activation function, is localized in a cell nucleus and conforms to the basic characteristics of transcription factors. It is found for the first time that overexpression of the CeNF-YA1 gene can significantly improve the grease content of arabidopsis seeds and leaves; therefore, the technical scheme provided by the invention can be used for improving the oil content of the plant seeds and the nutritional tissues, and shows the application prospect in improving the oil content of the seeds and the nutritional tissues.

The invention belongs to the technical field of biology, particularly relates to the technical field of plant genetic engineering, and more particularly relates to application of an MYC gene in regulation and control of chloroplast development and composite stress resistance. Specifically, the invention innovatively discovers that the combined action of warm and JA can significantly induce seedling cotyledon chloroplast dysplasia, and deletion / reduction of MYC gene expression can significantly inhibit chloroplast dysplasia of plants under the combined action of warm and JA. The discovery provides guidance for remarkably improving plant seedling chloroplast development in a complex dynamic environment and improving the seedling survival rate and photosynthetic productivity, can promote optimization of a chloroplast artificial regulation and control technology, and realizes directional design of efficient photosynthetic organs in facility agriculture and an artificial photosynthetic system.

The invention provides a gene module analysis method and device, equipment and a storage medium, and relates to the technical field of space transcriptomics. The method comprises the steps of obtaining space-time group chip expression data, performing linearization processing, and performing sliding window cutting to obtain a plurality of window units arranged according to a space sequence; calculating gene function activeness and constructing a matrix; clustering and grouping are carried out to obtain window groups; performing difference analysis screening on the window groups to obtain a difference expression gene set; and performing gene module analysis to obtain a functional gene module. According to the method, through an integrated processing flow of structure linearization, sliding window cutting, activeness quantification, clustering analysis and module identification, fine extraction and function reconstruction of spatial expression information in the curled tissue are realized under the condition that an additional algorithm or external data is not introduced; and the practicability and research value of the spatial omics data in a complex organization structure are improved.

The invention discloses a neural network calculation method and device for gene expression regulation and control analysis, and relates to the technical field of bioinformatics, and the method comprises the steps: obtaining first feature data and second feature data; constructing an input feature comprising a plurality of regulation and control hierarchies; and inputting the input features of the plurality of regulation levels and the second feature data into the target neural network model, and outputting a prediction result of the gene expression state. According to the neural network calculation method provided by the invention, chromatin accessibility and three-dimensional space interaction data are deeply fused through a dynamic routing module, so that the problem of'black box 'which is inaccurate in prediction and difficult to explain in a traditional deep learning model is solved in a mode of explicitly simulating a real biological regulation mechanism; and a key gene regulatory pathway can be accurately identified.

The invention discloses a differential gene regulation and control network reconstruction method based on mutual information and a redundancy regulation and control filtering system. The method comprises the following steps: firstly, collecting gene expression data under two or more conditions, respectively calculating mutual information of gene pairs under each condition, and screening the gene pairs with obvious mutual information difference as candidate regulation edges; furthermore, a redundancy regulation and control relation caused by the intermediary variables is identified and eliminated through calculation condition mutual information, and finally a difference regulation and control network with high credibility is constructed. The system comprises a data preprocessing module, a mutual information calculation module, a redundancy indirect regulation and control effect filtering module, a regulation and control direction judgment module, a network construction and threshold optimization module, a difference network construction module and an output and visualization module. The method can effectively improve the biological interpretability and inference accuracy of the network, and is widely applied to the bioinformatics fields such as disease mechanism research, regulatory factor identification and multi-omics integrated analysis.

The invention discloses a single cell space transcriptome data analysis method, device and system, and a storage medium. The method comprises the following steps: acquiring single cell space transcriptome data; the spatial transcriptome data comprises a gene expression map and spatial site coordinates; constructing a graph structure considering gene expression similarity and spatial position continuity on the basis of the data, and performing data representation on a gene expression graph by using an adversarial auto-encoder; in combination with a graph neural network, robust potential characterization is learned, training loss is constructed through reconstruction of a gene expression map, and meanwhile, a clustering prediction result of spatial sites is obtained in combination with mcluster clustering. By adopting the technical scheme of the invention, the spatial clustering analysis with higher precision can be realized, and the key spatial functional region in the biological tissue can be identified.

The invention relates to the technical field of crossing of bioinformatics, artificial intelligence and plant genomics, and discloses a plant single cell gene expression prediction method, system, device and medium. A plant single cell gene expression prediction model realizes dynamic feature fusion of a DNA sequence and chromatin accessibility signals through a gated cross attention mechanism; the problem that a traditional single-mode model cannot model regulation and control dynamic association is effectively solved, and the result interpretability is enhanced; a hybrid expert system and a load balancing design are adopted to significantly improve the recognition capability of the model for rare cell types, and a decoupling prediction head design supports efficient transfer learning; a DNA long sequence processing mechanism and nucleosome scale feature coding ensure cross-species compatibility; an end-to-end automatic process and a dynamic parameter optimization framework greatly improve the practicability; a'prediction-verification 'closed-loop support system can be constructed for molecular breeding, and high-precision and interpretable prediction of plant single-cell gene expression is realized.

The invention provides a kiwi fruit transcription factor and application thereof in kiwi fruit canker, and belongs to the technical field of genetic engineering. The invention provides a transcription factor AcWRKY50, the nucleotide sequence of the transcription factor AcWRKY50 is shown as SEQ ID No.1, and the AcWRKY50 is positioned in a cell nucleus and has transcription activation capability. The AcWRKY50 disclosed by the invention can continuously respond to Psa infection, after Psa pathogenic bacteria infection, the expression of the AcWRKY50 gene is rapidly activated and continuously up-regulated, and after the AcWRKY50 gene is over-expressed, the resistance to Psa can be improved. Meanwhile, MeJA negatively regulates the resistance of the kiwi fruit to the Psa, and the kiwi fruit germplasm can be innovated based on the transcription factor disclosed by the invention.

The invention discloses a plant immunomodulatory gene RDP as well as an expression vector and application thereof. The inventor finds a plant immunomodulatory factor gene RDP from potatoes, after a corresponding sequence is obtained through cloning, agrobacterium competent cells are transferred into nicotiana benthamiana, it is verified that the plant immunomodulatory factor gene RDP can be successfully expressed in other plants, and it is verified that the pathogenic effects of various phytophthora are good. The gene is proved to be capable of effectively improving the disease resistance of the nicotiana benthamiana after being expressed. Through objective evaluation of an agrobacterium tumefaciens-mediated transient expression system, it is found that the plant immunomodulatory factor RDP can induce plants to generate resistance, the gene can be directly introduced into the plants through a transgenic technology due to the powerful function of the gene, disease-resistant varieties are developed and cultivated, and the gene has great significance in prevention and treatment of plant diseases.

The invention discloses a protein complex identification method based on knowledge enhancement graph comparative learning, and belongs to the technical field of bioinformatics. Edge trimming is performed by using a gene expression profile and subcellular localization data, so that a knowledge enhancement PPI network is constructed; and incorporating the molecular function and the biological process as network attributes as attributes for enhancing the network. Graph structure enhancement is applied to knowledge enhanced PPI attribute networks, and multiple perturbation views are generated with diverse random perturbation policies including edge addition, edge discarding, and feature masking to help mitigate data sparsity. A perturbation view generated by graph structure enhancement is coded through a randomized graph convolutional network layer, so that multi-scale features are extracted, key PPI interaction is reserved, and meanwhile prediction performance is improved. And finally, the original PPI network is weighted again, and the protein complex is identified by adopting a core-affiliated strategy.

The invention provides the cassava low-temperature-resistant MeSR45-2 gene cloned from cassava for the first time, the expression of the MeSR45-2 gene in cassava is inhibited under low-temperature stress, and research shows that the gene can significantly improve the low-temperature resistance of cassava, reduce the malondialdehyde content, proline cumulant and the like in cassava, reduce leaf damage under low-temperature treatment and improve the yield of cassava. Terminal buds under low-temperature treatment are not affected and can normally grow, and expression of various protein genes is regulated and controlled. The invention provides a new candidate gene for research on improvement of plant low temperature resistance and the like, and also provides a new gene resource for cultivation of a new variety of low temperature resistant cassava and construction of a new variety of transgenic cassava.

The present invention relates to a compound for inducing the expression of the anti-aging gene klotho and a preparation method therefor. The compound represented by Chemical Formula 1, according to the present invention, has an excellent effect of increasing the expression level of the klotho gene which is a gene associated with aging, and thus can be useful for a pharmaceutical composition, cosmetic composition or food composition for preventing skin aging, inhibiting cellular senescence or preventing, treating alleviating a vascular aging-induced disease or a renal disease.

Provided herein are methods, kits and compositions for detecting an analyte of interest to interrogate spatial gene expression in a sample using templated ligation.

The invention provides a multi-slice spatial group data alignment and data enhancement method based on deep learning, which comprises the following steps: collecting slices of different tissues in a plurality of development stages, and obtaining gene expression data of a single cell level of each slice and spatial position information of each cell in the tissues by utilizing a spatial transcriptomics technology; based on the gene expression data and the spatial position information of each slice, constructing a spatial diagram by combining a K-nearest neighbor method and a circular neighborhood construction method, and mapping the spatial diagram to a shared embedding space by using a DGCNN network to obtain embedding distribution; respectively sampling the embedding representation of each cell point from the embedding distributions of the two slices, and outputting the probability of a real sample by using a discriminator of the generative adversarial network; spatial alignment of the two slices is achieved by minimizing the difference between the probability distributions of the two slices. According to the method, accurate spatial alignment is realized by integrating spatial information of different slices, and data enhancement is carried out by aggregating information of adjacent slices into a target slice.

The invention discloses a method for treating piglet damp-heat diarrhea through multi-omics combined analysis. According to the method, faeces metabonomics, intestinal transcriptomics and intestinal flora 16s analysis are adopted, transcriptome data, metabolome data and intestinal flora data are screened according to a prime difference standard, then transcriptomics of a model group and a control group, faeces metabonomics and intestinal flora are subjected to conjoint analysis, an intersection is taken, and the faeces metabonomics of the model group and the control group, the faeces metabonomics of the model group and the control group and the intestinal flora of the model group and the control group are subjected carrying out conjoint analysis on transcriptomics of the Model group and HQ-M, faeces metabonomics and intestinal flora, and then taking an intersection; the method comprises the following steps of: selecting a plurality of metabolites and florae from a plurality of intestinal florae, respectively obtaining intersections, screening related genes, searching gene FPKM expression quantity in transcriptomics, and screening corresponding metabolites and florae in metabonomics and intestinal florae to obtain a gene-flora-metabolite related network diagram. Multi-omics combined analysis shows that the piglet diarrhea due to damp-heat is mainly manifested by inflammation and glucose and lipid metabolism disorder.

The invention discloses a spatial transcriptome data analysis method based on artificial intelligence, and belongs to the technical field of spatial transcriptomics data analysis. Firstly, self-adaptive normalization and hypervariant gene screening preprocessing are carried out on original gene expression data; then constructing a hierarchical map integrating spatial proximity and transcription similarity, and ensuring the connectivity and robustness of the map through a dynamic radius pruning and neighborhood inheritance strategy; dividing positive and negative sample sets based on the atlas, and inputting a type modulation contrast graph auto-encoder for training; and finally, spatial domain identification and downstream function analysis are completed based on the low-dimensional potential representation or reconstructed gene expression matrix output by the model. The method effectively improves the accuracy and stability of spatial domain recognition, adapts to multi-technology-source data, enhances the biological interpretability of model output, and can be widely applied to biomedical scenes such as tumor microenvironment analysis and organ development research.