14 results about "Functional profiling" patented technology

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 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.

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 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 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.

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 an electromechanical system architecture forward design method based on a servitization thought, and belongs to the field of airplane electromechanical system design. The connection of requirements, functions, services, logic and physical architectures is realized through model-based system engineering (MBSE). Specifically, the method comprises the following steps of: establishing a demand structured model by using a SysML language, analyzing a target system function to obtain a service scheme meeting a function demand, realizing service logic through a logic layer state machine, and performing joint simulation with a physical layer simulation model to form'demand-function-service-logic-physics' full-link mapping taking the model as a clue; and the forward design of the system architecture is realized.