33 results about "Functional profiling" patented technology

The invention discloses an enterprise service platform intelligent management and control method and system based on function analysis, and relates to the technical field of platform intelligent management and control, and the method comprises the steps: collecting the calling frequency, resource occupancy rate, response time delay, user behavior track and abnormal event data of a function module, carrying out the standardization and time sequence verification, and constructing a multi-dimensional operation data flow. Constructing a functional behavior model based on a graph neural network, extracting module operation features and structural dependence, dynamically generating a functional thermodynamic scoring graph, and realizing visual display of module loads and abnormal hotspots; and constructing a functional twin copy for the key module, simulating a management and control strategy in an isolated simulation environment, and obtaining feedback. Constructing a multi-level management and control strategy generation matrix based on feedback, generating and optimizing candidate strategies, dynamically deploying, continuously monitoring and automatically adjusting; the system adopts a hierarchical rollback mechanism to realize strategy self-adaptive rollback in case of exception, so that stable and reliable operation of the platform is guaranteed.

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.

The invention relates to a territorial space multi-level function data analysis processing method and device, belongs to the technical field of land space distribution data processing, and solves the problems of inconsistent function positioning of different types of territorial spaces and insufficient accuracy of analysis result data in an existing territorial space function analysis method. The invention discloses a territorial space multi-level function data analysis processing method and device. A land parcel is strengthened according to a purpose-function conversion matrix so as to update a function identification unit of the land parcel; quantifying the spatial distribution density of each type of POI of the land parcel according to the kernel density of the POI data; calculating the distribution frequency of different POI types in each function type in the function identification unit; in combination with a kernel density analysis result and a frequency density analysis result, carrying out weighted calculation and standardization processing on the spatial function value of each function identification unit; and determining a data analysis result of each function identification unit in each function hierarchy framework. According to the method, the land space layering is analyzed and processed, so that the accuracy of analysis result data is improved.

The invention provides a subcellular level space transcriptome function analysis method and system, and relates to the field of bioinformatics, the method comprises the following steps: automatically processing core information of a sample, and optimizing space transcriptome expression matrix data to realize expression matrix data reception and automatic processing; timed polling and the like are added to realize automation of standard analysis from a space gene expression matrix to a space transcriptome, and gene ID conversion, cell unit type selection and cell unit selection are performed according to expression matrix data to obtain data after selection; and according to the converted and selected data, carrying out statistics on spatial data features, and visualizing the data features. According to the method, through a multi-module automatic process, the analysis efficiency, accuracy and biological interpretation of space transcriptomics and single cell data are remarkably improved, and the method is suitable for multi-sample, high-resolution and big data analysis scenes.

A method for segment preserving protein design includes determining, within a protein structure having a first sequence of residues, one or more fixed segments and adjustable segments. The protein structure may be identified as having a desired property. A protein design computational model may be used to generate a second sequence of residues comprising at least one of a corruption and a length change to the first adjustable segment. The protein design computational model may be further used to generate a modified protein structure having the second sequence of residues. The second sequence of residues forming the modified protein structure includes the fixed segments present in the first sequence of residues. Structural and / or functional analysis may be performed to determine whether the modified protein structure also exhibits the same desired property as the protein structure. Related systems and computer program products are also provided.

The invention relates to a method for functional analysis of a source system (1), wherein a syntax tree model (3) is generated from the program code data of the source system (1). In order to propose a method for functional analysis of a source system (1), in particular with extensive program code data, which method makes it possible to better identify interrelated functional units and, with high result quality and at the same time low resource requirements, to improve further processing by means of a large language model, the invention provides that a syntax analysis unit (4) generates a syntax embedding model by decomposing the syntax tree model (3) into individual syntax element embeddings (5), each representing a syntax element, and stores said syntax embedding model in a syntax embedding model memory (6), and that a language analysis unit (8) generates a language embedding model by decomposing the program code data into individual language element embeddings (9), each representing a language element, and stores said language embedding model in a language embedding model memory (10), whereupon, by means of a query unit (12), at least one query embedding (13) is generated from a query (11) representing a functional element of the source system (1) and those syntax element embeddings (5) and language element embeddings (9) which lie within a predefined range of similarity to the query embedding (13) are retrieved from the syntax embedding model memory (6) and the language embedding model memory (10), whereupon the syntax elements represented by the retrieved syntax element embeddings (5) and the language elements represented by the retrieved language element embeddings (9) are transferred as result elements (14) to an output unit (15), which generates therefrom a functional description dataset (16) and outputs the latter.

The present invention discloses a design failure mode and effect analysis method based on knowledge graph and large model retrieval enhancement, comprising the following steps: Step 1: Planning and preparation stage; Step 2: Structural analysis and functional analysis stage; Step 3: Failure analysis stage: Using graph knowledge reuse components to process input data and retrieve relevant information from the full-cycle knowledge base, the data is then processed and constructed by the industrial knowledge software system to obtain a knowledge graph; Based on the knowledge graph, the large model retrieval enhancement method deeply analyzes the input information, extracts relevant information from the knowledge graph in combination with the large model prompt learning method, and generates failure analysis results; Step 4: Risk analysis and optimization stage: Determine the issues that need to be addressed first, propose and implement improvement measures; Step 5: Result documentation and system integration stage. The present invention also discloses a design failure mode and effect analysis system based on knowledge graph and large model retrieval enhancement.

The invention provides an intelligent drug research and development method and platform, computer equipment and a storage medium. The method comprises the following steps: constructing a database to store drug data information; configuring codes used for database query and different kinds of function analysis on the medicine data information; constructing an intention recognition model and carrying out question and answer training based on user intention recognition; constructing a plurality of APIs (Application Program Interface), and enabling the APIs to correspond to different types of function analysis; obtaining research and development demand information input by the user, and performing intention recognition through the intention recognition model to obtain a target intention of the user; and calling a corresponding API interface according to the target intention to obtain drug data information or a data processing result required by the user, and feeding back the drug data information or the data processing result to the user through a front-end interface. According to the scheme, accurate research and drug design and analysis of drug discovery items can be realized, and non-professionals can also participate in research and development work, so that improvement of research and development efficiency is facilitated, and research and development time and human resource cost are reduced.

Disclosed herein are methods, compositions, systems, and kits related to functional testing of polypeptide-target interactions, such as antigen / immune receptor interactions, in a single-cell format.

The present application relates to a kind of metabolic pathway extension network based on structural feature automatical establishment method, belong to bioinformatics and computational chemistry technical field.The purpose is to solve the problem of existing KEGG database incomplete, annotation lag of metabolite.Method includes: obtaining KEGG skeleton and modified group construction seed library;Through substructure matching and set difference calculation to determine the attribution of derivative;Iterative expansion forms structure association set;Combining stereochemistry rule and mass difference verification screening derivative;Merging KEGG reaction and extended relationship constructs network, and remove redundant path by graph theory method, finally output extended pathway network.The method greatly improves the annotation rate of metabolite pathway, supports in-depth functional analysis of metabolomics data.

The invention relates to the technical field of nuclear power, and provides a natural circulation flow analysis method, which comprises the following steps of: performing functional analysis on a main loop, identifying modeling objects with different functions, summarizing thermal-hydraulic common characteristics of the modeling objects, and establishing a unified local segment class. Through an object-oriented instantiation mechanism, a function model of each modeling object is quickly generated, and then a complete main loop system model is constructed. Automatic exchange of physical quantities such as pressure, flow, enthalpy value, temperature and heat flow among local sections is realized by adopting a connector mechanism, and interface logic does not need to be written manually. The method supports fusion of the thermal hydraulic model and the point reactor neutron dynamics model, unifies the simulation environment, remarkably improves the modeling efficiency, flexibility and model reusability, is suitable for main loop natural circulation flow calculation, design optimization, operation analysis and safety evaluation, and provides efficient and accurate modeling and simulation support for a nuclear reactor main loop.

The invention discloses a genome editing and detecting system for recognizing a DNA target based on TDP-43 dimerization and application of the genome editing and detecting system, and belongs to the technical field of molecular biology. FokT fusion protein construction, cell transfection and functional labeling, FokT-Seq detection through high-throughput sequencing, target annotation and functional analysis and disease mutation experience verification are carried out, and the genome editing and detecting system for recognizing the DNA target based on TDP-43 dimerization is obtained. Specific recognition and functional marking on the TDP-43 dimerization dependent DNA binding site are achieved for the first time, and traditional ChIP-Seq, CUTamp, CCTP-Seq, CCTP-Seq, CCTP-Seq, CCTP-Seq; a conformational state monomer or dimer when TDP-43 is combined with DNA cannot be judged by methods such as FOkI, FOkI is only activated in a dimerization state, and only a DNA target of TDP-43 combined in a dimer form is marked, so that the structure specificity of recognition is remarkably improved, and false positive binding site interference is avoided.

The invention belongs to the field of bioinformatics and computational biology, and provides a bioinformatics multi-omics association analysis method based on a co-disease model. Comprising transcriptome range correlation analysis based on GWAS and GTEx, causal analysis in a transcriptome range based on different Bayesian models, and screening and functional analysis of co-disease hub genes based on co-localization analysis and transcriptome data. According to the method, a complete technical system from macroscopic population queue genome analysis to human body multi-tissue fine positioning and then to microscopic cellular level gene target screening and verification is established, and a reliable target gene screening process and a mechanism analysis scheme are provided for precise prevention and treatment of metabolism and vasoplasmosis.

The invention belongs to the field of system engineering, and particularly relates to a model-based information system modeling method, which comprises the following steps of: S1, determining an operation scene and a benefit-critical party of an information system, and constructing a first demand analysis chart associated with the operation scene and the benefit-critical party; s2, determining behaviors of all the benefit critical parties in all the operation scenes, and forming a second demand analysis chart containing demand entries; s3, layering the functions and composition of the information system, determining the transfer relationship of substances, energy or signals among the functional layers to form a first functional analysis chart, and determining the hierarchical architecture of each composition layer to form an architecture analysis chart; step S4, determining information circulation of each function among a plurality of nodes in each layer of the hierarchical architecture to form a second function analysis chart; and S5, based on the hierarchical architecture, determining a performance parameter relationship of adjacent hierarchies, and constructing a performance analysis chart. The method can effectively support the demand design of a complex information system and improve the scheme design quality.

The invention belongs to the technical field of brain region function analysis, and particularly relates to a core brain region screening method and system. The core brain region screening method comprises the following steps: step 1, data acquisition and preprocessing; step 2, feature map construction and generation-discrimination network training; step 3, candidate sample generation, post-processing and quality evaluation; and 4, performing multi-algorithm feature consensus screening and stability evaluation. According to the core brain region screening method, firstly, class condition amplification with graph constraints is used, multi-index quality gating is assisted, then the reproducibility of feature selection is improved through multi-algorithm consensus screening and stability measurement, and finally, a stable and auditing judgment result is output in combination with multi-model integration. Therefore, the brain region screening performance and the generalization stability are remarkably improved under the scenes of scarcity of samples, class imbalance and high-dimensional structured data.

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.

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.

The invention discloses a blood vessel structure and function coupling analysis method and system based on multi-mode MRI, and belongs to the field of medical image analysis and computational physiology. According to the method, 4D Flow MRI hemodynamic data and blood vessel spatial configuration features are fused, and the problem that in the prior art, structure and function analysis is split, and the coupling relation between the structure and the function cannot be revealed is solved. The method comprises the core steps of blood vessel image acquisition and preprocessing, structural feature extraction, functional parameter calculation, coupling analysis and result output, and the system correspondingly comprises functional modules. According to the method, automatic registration and collaborative analysis of structural-functional data are realized, comprehensive support can be provided for diagnosis of diseases such as liver cirrhosis and portal hypertension and TIPS surgical planning, and clinical prediction accuracy and diagnosis and treatment efficiency are improved.

This invention discloses a functional analysis system for skeletal muscle organoids and its applications. The core of the system lies in its use of computer vision technology to automatically analyze motion videos of calcium-ion fluorescently labeled skeletal muscle organoids under stimulation. The system automatically identifies organoid regions of interest (ROIs) through specific image processing algorithms (such as adaptive threshold fusion and contour detection), extracts time-series data of calcium signal intensity, and calculates characteristic parameters such as relative fluorescence change rate and peak frequency, ultimately outputting a quantitative functional assessment report. This assessment scheme is low-cost, high-throughput, objective, and accurate, overcoming the technical bottleneck of existing organoid functional assessments that rely on subjective manual analysis or expensive specialized equipment. It is compatible with various culture systems, greatly promoting the large-scale application of skeletal muscle organoids in drug screening and toxicity testing.

The invention discloses a method for screening, identifying and functionally analyzing a poplar latex protein family at a whole genome level by using multiple bioinformatics methods, and relates to the field of plant gene identification and screening. The method comprises the following steps: performing preliminary screening, re-modeling, re-screening and identification on an obtained poplar whole genome file, an annotation information file, a protein sequence file and an MLP protein family structure file to obtain a final poplar MLP gene family member; on-line physicochemical property analysis software is used for carrying out predictive analysis on physicochemical properties, and predictive software is used for carrying out possible function analysis on a gene structure, a conservative structural domain, a promoter region cis-acting element and protein subcellular localization; evolutionary trees of the poplar MLP family members and the arabidopsis MLP family members are constructed through evolutionary tree software, and evolution analysis and classification of the poplar MLP family members and the arabidopsis MLP family members are analyzed. According to the method, the interested poplar MLP family gene can be effectively and quickly screened, and the time and cost of molecular means screening are greatly reduced.

The invention relates to the technical field of biology, and discloses an application of a millet KQL12033 gene in a seed development process. The Setaria italica KQL12033 gene belongs to an ALOG gene family, and the Setaria italica KQL12033 gene has a nucleotide sequence as shown in SEQ ID NO: 1. A millet ALOG gene family is screened and identified through a bioinformatics technology, the expression quantity trend of ALOG gene family members in the seed development process is further analyzed in combination with a high-throughput sequencing technology, and it is determined that the KQL12033 gene participates in the millet seed development process. The invention lays a foundation for large-scale identification and functional analysis of seed development related genes.

This application is a numerical-computation-based digital R & D method and system for the lightweighting of power tools, belonging to the field of power tool optimization. Aiming at the obvious limitations in the R & D of existing table saw power tools, a numerical-computation-based digital R & D method for the lightweighting of power tools is provided: According to the division of functional roles and connection relationships, table saw power tools are disassembled into different functional components; Standardized functional analysis modules for each functional component are constructed based on the finite element analysis method; A digital 3D model of the functional components of the table saw power tool is obtained, and the surface feature information and load parameters obtained by the interaction of the corresponding functional components are set. By outputting the stress, strain, and deformation data of the corresponding functional components and converting them into the corresponding cloud map results. This application modularizes each functional component of the power tool, can adapt to and verify different application scenarios and customer requirements, reduce the difficulty of pre-processing settings for finite element analysis, and can also reduce costs and technical thresholds and shorten the R & D cycle.

The present invention discloses a method for identifying ancient metagenomic fragments based on paired-end sequencing and its application, belonging to the technical field of gene detection. The present invention includes steps such as preprocessing, alignment, annotation, and functional analysis of sequence data. By performing efficient and accurate data processing and analysis on ancient metagenomic fragments, it can reveal the genetic information of ancient biological populations and their evolutionary history, providing important data support and technical guidance for fields such as archaeology, genetics, and environmental science. The present invention can not only overcome the limitations of traditional methods, adapt to different types of ancient samples, but also provide more comprehensive genetic information, promoting the in-depth development of ancient metagenomic research. Through the development and application of the new method, researchers will be able to more accurately analyze the structure and function of ancient microbial communities.

Disclosed is an analytical platform for profiling and functional analysis of proteomes, which can unveil new biological insights potentially useful for instigating novel therapeutic interventions. The disclosed analytical platform for proteome profiling is constructed by integrating plasmonic biosensor microarrays with tandem-ion mobility spectrometry. The disclosed analytical platform can separate, identify, and characterize highly similar proteoforms as well as low abundance proteoforms from plasma or other samples.

Disclosed is an analytical platform for profiling and functional analysis of proteomes, which can unveil new biological insights potentially useful for instigating novel therapeutic interventions. The disclosed analytical platform for proteome profiling is constructed by integrating plasmonic biosensor microarrays with tandem-ion mobility spectrometry. The disclosed analytical platform can separate, identify, and characterize highly similar proteoforms as well as low abundance proteoforms from plasma or other samples.

The present application belongs to the technical field of bio-information analysis, and provides a method for identifying lineage-specific expanded gene families. The present application is a method for screening and identifying lineage-specific expanded genes in different subfamilies by using orthology analysis. The method is simple to operate, requires a small amount of data, and the analysis software is easy to learn to operate. The screened genes are well representative, which lays a foundation for future large-scale identification and functional analysis of lineage-specific genes.

The invention discloses a non-cloning genomics analysis method based on a SCoT marker, which can directly restore 01 data into a simulation sequence of PCR (Polymerase Chain Reaction) according to an electrophoretogram by adopting a new data processing and statistical analysis method'primer replacement method 'without cloning and sequencing after completing SCoT electrophoresis on a to-be-detected target. Homologous genes are directly retrieved through bioinformatics analysis of SCoT sequences, classification analysis and function analysis are carried out according to the copy number, existence and distribution of SCoT differential genes, and the molecular basis of genetic diversity variation of genomes is completely revealed. According to the method, SCoT marker analysis is improved into SCoT omics analysis, bioinformatics analysis can be carried out by utilizing genomics big data, a molecular basis of genomic genetic diversity variation among different materials is disclosed, and the method has important significance and wide application prospects in improving the breeding efficiency, accelerating the breeding process and improving the fundamental research theory level.

1. The name of the product under this design: Coagulation Analyzer (UG500). 2. Purpose of the product with this design: used for functional analysis of coagulation, anticoagulation, etc. on whole blood samples and for medical clinical diagnosis. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The present invention discloses a method and device for predicting the developmental toxicity of chemicals based on multimodal fusion. The method comprises the following steps: obtaining the data required for the model (SMILES of the compound); saving the SMILES of the compound into the device; the device automatically calls the preset data files, Python and related libraries in the environment to calculate the data of three modes of chemical descriptors, biological activity and batch key molecule docking, and generates thousands of features that are further called and input into the pre-trained developmental toxicity prediction model (multimodal fusion modeling); the output result of the developmental toxicity prediction model is the developmental toxicity risk prediction value and suspicious risk structure of the chemical source of the data. If the predicted value is greater than 0.5, the genes corresponding to the proteins with higher docking scores of the key molecule docking are simultaneously screened out for annotation and functional analysis, so as to achieve the purpose of segmented prediction, which is of great significance for the identification of emerging chemicals.

The invention relates to scRNA-Seq, in particular to a cell annotation method based on pulmonary fibrosis scRNA-Seq data, which can efficiently identify and distinguish different cell types in pulmonary fibrosis and provide accurate cell classification and functional analysis. The FPCAM platform supports the preprocessing, annotation and visualization of single cell transcriptome data, reveals the cell heterogeneity and the change of a signal transduction pathway in combination with omics data analysis, and deeply understands the molecular mechanism of pulmonary fibrosis. Through integration of multiple omics data, theoretical basis and technical support are provided for accurate treatment and new drug research and development, and accurate medical research of pulmonary fibrosis is promoted. The invention provides an innovative and efficient tool, and an important technical route and solution can be provided for research on pulmonary fibrosis and other unicellular omics related diseases.