21 results about "Expression analysis" patented technology

The application belongs to the technical field of biological detection, and discloses a screening method of respiratory tract infection related biomarkers based on macro-transcriptomics. The application performs macro-transcriptome sequencing on respiratory tract infection samples with different clinical phenotypes, performs data quality control, alignment, transcript quantification, retains pathogen and host information, and then identifies genes stably expressed or significantly changed in different groups by combining differential expression analysis and co-expression analysis, obtains potential biomarkers, and obtains the biomarkers by taking the intersection genes of three machine learning algorithms of LASSO algorithm, random forest model and SVM model. The application provides a screening method of biomarkers for rapid and accurate identification of respiratory tract infection.

This invention relates to the field of artificial intelligence technology and discloses a method for generating instant empathetic responses for robots based on micro-expression triggers. The method includes collecting facial micro-expression data of the interacting object, generating standardized micro-expression data through preprocessing, generating feature vector data based on micro-expression feature extraction, generating classification data by combining emotional state analysis, generating trigger signals for empathetic responses, generating empathetic response text data using natural language generation technology, and outputting instant empathetic responses through speech synthesis. Simultaneously, the micro-expression analysis model is optimized based on interaction feedback data. This invention ensures the reliability of the data foundation for generating empathetic response trigger signals, guarantees the real-time performance and reliability of interactive responses, and improves the friendliness and overall effect of robot interaction.

The present application relates to the technical field of image intelligent analysis, and particularly relates to a breast cancer medical image intelligent analysis system and method fusing deep learning. The method comprises the following steps: acquiring medical image data of a target breast region, and determining breast structure distribution data based on the medical image data; identifying the radial distribution characteristics of breast gland ducts according to the breast structure distribution data, and constructing duct direction constraint data based on the radial distribution characteristics of the gland ducts; transmitting the duct direction constraint data to a preset deep learning model, performing direction-sensitive feature expression analysis on the breast structure distribution data, and obtaining direction response feature data along the main direction of the ducts and deviating from the main direction of the ducts; and determining structure abnormal regions in the breast medical image based on the direction response feature data. The present application realizes the representation ability of complex structure distribution and its change characteristics by intelligent analysis of breast cancer medical images.

This invention belongs to the field of bio-agriculture and relates to nitrogen-responsive genes during the rice heading stage. HDRN1 Applications. Knocking out nitrogen-responsive genes during the rice heading stage. HDRN1 Applications in advancing the heading stage of rice, improving the nitrogen response sensitivity of rice, breeding rice varieties that are sensitive to nitrogen fertilizer, or breeding early-maturing rice varieties. This invention reveals the TBL family genes for the first time. HDRN1 It participates in the nitrogen signaling pathway and negatively regulates the heading stage of rice. This was demonstrated through BSA-seq, database expression analysis, and mutant phenotypic validation. HDRN1 It is a novel nitrogen-responsive heading-stage regulator. This invention constructs... hdrn1 The mutant exhibited a significantly earlier heading date than the wild type under both low and high nitrogen conditions. Simultaneously, the mutant showed enhanced nitrogen response sensitivity, indicating... HDRN1 The loss of function makes the plant more sensitive to changes in nitrogen levels, which can be used to breed varieties that are sensitive to nitrogen fertilizer and avoid varieties that are too vegetative and mature late.

The application provides a long video micro-expression detection and recognition model construction and application method and an electronic device. A pupil dynamic feature is introduced to cooperatively modulate a facial motion feature, and a long video micro-expression detection and recognition model is constructed, so as to solve the problems that in the prior art, long video micro-expression analysis mainly depends on a single facial motion mode, a weak micro-expression key moment is not sensitive enough, cross-modal response is not synchronous, and video level interval recovery stability is poor.

This invention belongs to the field of biotechnology and relates to a... OsFBX148 Application of genes in regulating plant cold tolerance. This invention reveals a gene in rice called... OsFBX148 Novel functions of the gene and its encoded protein were discovered. Tissue-specific expression analysis showed that the gene was highly expressed in rice roots, and its expression level was significantly upregulated by low-temperature stress. Targeted mutation was performed using gene editing technologies (such as CRISPR / Cas9). OsFBX148 The gene can significantly enhance the cold resistance of rice plants, indicating that the gene plays an important role in regulating the cold resistance of rice. This invention provides an important gene resource for the genetic improvement of cold resistance in rice, and has important application value for breeding crop varieties with enhanced cold resistance and ensuring food security in high-altitude and cold regions.

The application discloses a kind of mathematical learning behavior tracking method and system based on big data analysis, it is related to big data analysis technical field. Including: acquisition learner is generated in the multi-source behavior data of digital mathematical learning platform;Mathematical expression analysis is carried out to draft track, generate expression syntax tree sequence, carry out difference operation to the expression syntax tree of adjacent time step, extract atomic operation sequence;Using time series behavior encoder, output knowledge state evolution vector;The knowledge state evolution vector is aligned with the pre-constructed mathematical knowledge graph, the probability of mastering of learner on each mathematical rule node is calculated and weighted rule violation sequence is generated;Using dependent edge, the weighted rule violation sequence is reversely propagated, and the basic missing rule is identified;According to basic missing rule and mastery probability, personalized learning path recommendation is generated.The application realizes the accurate tracking of mathematical learning behavior and individualized teaching.

This invention belongs to the field of plant genetic engineering technology and discloses a method for constructing transgenic hairy roots with multi-gene co-expression of the tanshinone biosynthesis pathway. The method first constructs a multi-gene expression vector containing the SmCPS1, SmKSL1, and SmCYP76AH1 genes, and then introduces the multi-gene expression vector into Agrobacterium rhizogenes. Subsequently, recombinant Agrobacterium rhizogenes is used to infect tanshinone explants, and transgenic hairy roots are induced after co-culture, sterilization culture, and resistance screening. Positive hairy roots are then identified and their expression analyzed by PCR and qRT-PCR, achieving stable co-expression of key genes in the tanshinone biosynthesis pathway. This invention achieves a single co-transformation of multiple key genes, simplifies the multi-gene transformation process, reduces the risk of gene segregation and expression instability caused by multiple transformations, and can provide stable transgenic materials for research on the tanshinone biosynthesis pathway and the metabolic regulation of active components in tanshinone.

This invention proposes a method for regulating malt PYF based on gene expression during the malting process and its application, belonging to the field of bioengineering. It addresses the technical problems of existing malt PYF detection methods, such as limited detection targets, narrow applicability, and inability to guide subsequent malting processes. The technical solution includes steps such as gene screening, primer design, total RNA extraction, reverse transcription to prepare cDNA templates, multiplex PCR, PCR product electrophoresis, product fragment expression analysis, and prediction and improvement of malt PYF performance. This invention features short processing time, high detection efficiency, and high accuracy. It can accurately predict malt PYF performance during the malt production process and establish adjustment measures for the malting process based on the prediction results, ultimately achieving the goal of improving malt PYF performance. This invention can be applied to the improvement of malt PYF performance.

The embodiment of the application discloses a gene expression analysis method and device, electronic equipment and a readable storage medium, and belongs to the technical field of bioinformatics and the field of data processing. The method comprises the following steps: determining a first difference of a target gene in a target cell type based on an aggregate expression value of the target gene in the target cell type of a to-be-tested sample and a reference expression value of the target gene in the target cell type of a reference sample; determining a second difference of the target gene in the target cell type based on the first difference of the target gene in the target cell type and the first difference of the target gene in different cell types of the to-be-tested sample; and performing gene differential expression analysis based on the second difference of the target gene. According to the embodiment of the application, the influence of batch effects on gene expression analysis can be effectively reduced.

The application relates to the technical field of pathogen detection, and discloses a pathogen multiplex PCR rapid detection method based on GenomeLabTM GeXP multiplex gene expression analysis technology. A primer group composed of seven pairs of specific primers, one pair of positive control primers and one pair of universal primers is used to detect pathogens. The seven pairs of specific primers are respectively used for specifically combining with target genes of porcine fever virus, porcine reproductive and respiratory syndrome virus, pseudorabies virus, porcine parvovirus, porcine circovirus type 3, necrotic fusiform bacteria and porcine epidemic diarrhea virus. The 5' end of the universal upstream primer is provided with a fluorescent label. A two-step PCR amplification program is adopted, and rapid and accurate detection of the seven important pathogens, i.e. porcine fever virus, porcine reproductive and respiratory syndrome virus, pseudorabies virus, porcine parvovirus, porcine circovirus type 3, necrotic fusiform bacteria and porcine epidemic diarrhea virus, is successfully realized in one reaction system.

The application discloses a boiler fault prediction and diagnosis method based on operation thermal parameters, and belongs to the technical field of boiler monitoring; the method comprises the following steps: establishing a boiler fault simulation model, containing a virtual boiler structure, and constructing a three-dimensional positioning model with the center coinciding with the virtual boiler structure, which is used for expressing internal abnormal parts and forming abnormal expression blocks; constructing various boiler operation abnormal characteristics, driving the simulation model to simulate under various load conditions to obtain abnormal expressions; analyzing the abnormal expressions, extracting dynamic expressions of the abnormal expression blocks and corresponding operation thermal parameter groups, and establishing and saving the correlation between the two and the abnormal characteristics; and constructing a block dynamic expression analysis model based on the above, analyzing real-time operation thermal parameters, matching corresponding block dynamic expressions, and determining the boiler operation abnormal characteristics. The application generates abnormal samples through simulation and realizes accurate mapping of parameters and spatial block dynamics, thereby improving the accuracy and positioning precision of fault prediction.

The application provides an antigen epitope polypeptide and a paralichthys dentatus BMP2 protein specific antibody prepared by the antigen epitope, designs an antigen epitope through bioinformatics analysis, adopts a segmented recombination expression strategy to obtain BMP2-N and BMP2-C recombination proteins in view of the low expression efficiency of full-length BMP2 protein in a prokaryotic system, and uses the recombination proteins as immunogens to prepare polyclonal antibodies. It is verified through immunoblotting and immunofluorescence that the prepared antibodies can specifically recognize the paralichthys dentatus BMP2 protein, have high affinity and good reaction activity, and effectively avoid the problems of false negative or low signal caused by insufficient cross reactivity of the antibodies. On this basis, a BMP2 immunological detection kit is constructed, precise positioning and expression analysis of the BMP2 protein in mucous membrane tissues such as skin, gill and intestinal tract of the paralichthys dentatus can be realized. The antibody and the kit provide a reliable tool for studying the role of BMP2 in fish mucosal immunity, and have important scientific research value and application prospect.

This invention discloses genes GmISO5 Application of the gene in regulating the isoflavone composition of soybean seeds and its resistance to soybean mosaic virus. GmISO5 The nucleotide sequence is shown in SEQ ID NO: 1. This invention, through genetic analysis of isoflavone-related traits in soybean seed populations, identified candidate genes significantly associated with isoflavone content. GmISO5 Furthermore, expression analysis and functional verification clarified the close association between this gene and the isoflavone trait in soybean seeds. The study showed that... GmISO5 It can positively regulate the content and composition ratio of isoflavones in soybean seeds. This is achieved using genetic engineering techniques. GmISO5 GmISO5 Regulation can significantly alter the content of isoflavones and their components in soybean seeds, enabling targeted improvement of the functional components of soybean seeds. This provides important genetic resources and effective technical means for cultivating new soybean varieties with high isoflavone content and high nutritional value.

The application discloses a broad-spectrum disease-resistant gene Rpl-avh23 of Nicotiana plumbaginifolia, and an encoding protein and application thereof. The application separates a disease-resistant gene Rpl-avh23 from the Nicotiana plumbaginifolia, the full-length cDNA of the gene is 2154 bp, the nucleotide sequence is shown as SEQ ID NO:1; the protein encoded by the gene is an intracellular immune receptor protein with a full length of 717 amino acids, and the amino acid sequence is shown as SEQ ID NO:2. The application finds that the Rpl-avh23 gene can improve the resistance of plants to oomycetes, fungi and / or viruses through transcription mode analysis and plant expression analysis, and therefore, the disease-resistant gene Rpl-avh23 can be applied to improving the disease resistance of plants or plant breeding.

This invention discloses a joint expression localization and recognition method and apparatus based on aggregated features and dual anchoring. Addressing the need for fine-grained expression analysis of single faces in first-person view videos, it constructs an end-to-end deep learning framework to achieve unified localization and recognition of macro and micro expressions. The method first processes the acquired single-face video data through a frame-by-frame AU recognition network that aggregates local and global features. Combining the advantages of convolutional neural networks and visual Transformers, multi-scale features are extracted and AU codes are generated. Then, a dual-stream 3D convolutional network assisted by AU codes is used to fuse spatiotemporal features, combined with a multi-scale sliding window strategy and a feature pyramid network, and a dual anchoring mechanism is proposed to jointly locate expression intervals. Finally, video segments are extracted based on the localization results, and classification is completed through an expression localization and recognition network. This invention effectively solves the problems of multiple coexisting expressions, large duration differences, and difficulties in micro-expression detection in videos through local-global feature aggregation, dual-stream 3D convolutional networks, and dual anchoring strategies, significantly improving the accuracy and robustness of expression localization and recognition.

This invention relates to the field of bioinformatics and discloses a method and apparatus for analyzing important characteristic proteins of lipoprotein disorders based on deep learning and multi-target protein expression. The method involves obtaining the multi-round training weights of the first hidden layer in a lipoprotein disorder analysis model corresponding to each protein feature during multiple training rounds; determining the importance feature score for each protein feature based on the multi-round training weights; and identifying at least one important characteristic protein corresponding to lipoprotein disorders based on the importance feature score. By dynamically tracking the weight evolution of the first hidden layer in the lipoprotein disorder analysis model during multiple training rounds, the importance of protein features is precisely quantified. Important characteristic proteins highly correlated with lipoprotein disorders are screened based on the importance feature score, providing important characteristic proteins with strong biological interpretability for lipoprotein disorders.

The application provides a malt PYF performance prediction method based on barley gene expression in a malting process and an application thereof, belongs to the field of biology, and can solve technical problems of traditional malt PYF detection methods, such as complicated operation steps, long time consumption, and narrow application range. The prediction method specifically comprises the following steps: candidate gene screening, tracking gene screening, reverse transcription reaction, multiple PCR reaction primer design, RNA extraction, reverse transcription cDNA template preparation, multiple PCR reaction, PCR amplification product electrophoresis and expression analysis, and malt PYF performance prediction. By comparing the gene expression differences of standard malt and PYF malt in the malting process, tracking genes are selected in the large production process, and then by comparing the expression amounts of the standard malt and the to-be-detected malt and combining the evaluation standard, the malt PYF performance can be rapidly and accurately analyzed. The application can be applied to the field of malt PYF performance prediction.

A method for assessing a regular expression for vulnerability to ReDoS attacks includes receiving a regular expression for evaluating a string defined by ordered set of characters from an alphanumeric input device, and evaluating the regular expression for determining if a parsing operation of the string according to the regular expression results in a disproportionate resource consumption. The evaluation determines if the resource consumption constitutes a Regular expression Denial of Service (ReDoS) attack by providing a vulnerability indication of a single valid attack string, rather than attempting to find all possible attack strings. The valid attack string is defined by an input string for which evaluation based on the regular expression would result in disproportionate resource consumption.