298results about "Bioinformatics" patented technology

A database structure obtained by means of information retrieval, and a reasoning system, which structure and system specifically relate to a gut microbe knowledge graph system, comprising: a gut microbe knowledge graph consisting of a gut microbe knowledge base, a gut microbe and small-molecule drug therapy association knowledge base, and a clinical medicine database; and a multimodal uncertainty reasoning system, using the gut microbe knowledge graph. The gut microbe knowledge graph system predicts potential diseases, drugs, genes, etc., which are associated with gut microbes.

The invention belongs to the technical field of medical data processing and artificial intelligence, and particularly relates to a cardiovascular disease risk prediction system based on multi-modal fusion, which comprises a multi-modal data acquisition and preprocessing module, a cross-modal association graph construction module, a dynamic fusion and prediction module based on a graph neural network and an interpretability analysis module. By constructing a heterogeneous graph fusing prior knowledge and data driving and utilizing a graph attention network to perform multi-level dynamic feature fusion, deep integration and interaction of multi-modal data such as genomes, iconography, clinical and intestinal flora metabolism are realized, so that the accuracy and interpretability of cardiovascular disease risk prediction are improved.

The invention discloses a key marker gene-based intelligent cell type annotation method, which comprises the following steps of: constructing a static knowledge base by using known marker genes in a reference database, and endowing the marker genes with cell specific weights by using a TF-IDF method, so that the annotation accuracy and interpretability are improved. Meanwhile, under the condition that static matching is insufficient, the literature is understood through a large language model, mark information is extracted, dynamic completion of the knowledge base is achieved, the defect that updating of a traditional knowledge base is lagged is overcome, and good adaptability and expansibility are achieved. Besides, static and dynamic matching scores are fused in the annotation process, so that more robust cell type identification is realized, annotation requirements of multi-tissue, multi-species and novel cell states are adapted, high-precision and extensible cell type annotation can be realized in a scene with insufficient reference knowledge or a fuzzy sample, and the annotation efficiency is improved. And the method has good universality and practicability.

System and methods for alerting a healthcare provider to prescribed treatments having reduced or no effectiveness due to genetic composition is provided. A database containing treatments known to have reduced or no efficacy in persons having particular genetic markers is queried to determine whether any treatments prescribed by, or likely to be prescribed by, a healthcare provider to the patient are known to have reduced or no efficacy in persons having the same certain genetic markers as the patient. An alert indicating such information is displayed at a healthcare provider system.

The invention discloses an automatic construction system for a biological information analysis process, and the system comprises an intention understanding and semantic analysis module which is used for analyzing a natural language text inputted by a user into a structured task description meeting the requirements of a biological information analysis task; the knowledge graph and retrieval module is responsible for constructing a knowledge graph special for the bioinformatics field so as to provide knowledge retrieval and recommendation services; the process generation core module is used for receiving the structured task description, actively associating the knowledge graph with the retrieval module so as to supplement the field large model, and generating a biological information analysis target process language code; and the execution and monitoring module is used for guaranteeing workflow execution, full-life-cycle state monitoring, real-time fault diagnosis and intelligent self-healing decision making of target process language codes. According to the system, the executable analysis process can be directly generated according to the natural language requirement of the user, the tool compatibility and parameter validity are verified through the borrowed knowledge graph before execution, the dependency on the programming ability of the user is greatly reduced, and the process operation reliability is improved.

The application is suitable for the technical field of germplasm resources, and provides a germplasm resource data management system.The system comprises: an approval and registration sample management system, a resource survey collection management system, a germplasm resource library position management system, a germplasm resource phenotype database and a germplasm resource genotype database, the approval and registration sample management system manages data of crop standard samples; the germplasm resource phenotype database stores phenotype data of crop germplasm resources; the germplasm resource genotype database stores genotype data of crop germplasm resources; the germplasm resource library position management system manages data of crop germplasm resources; the phenotype data of crop germplasm resources, the genotype data of crop germplasm resources and the data of crop germplasm resources are corresponded through library number coding.The application can scientifically manage crop germplasm resource data, and can also realize internet sharing of crop germplasm resource data.

Provided herein is a recombinant polyclonal protein library (RPP) generated, at least in part, by an in silica method. Also provided are methods of using the RPP.

The invention is directed to methods for massively parallel template-free enzymatic synthesis of a plurality of different polynucleotides of predetermined sequences. In one aspect, methods of the invention employ large scale arrays of reaction sites each associated with at least one working electrode for controlling deprotection and deblocking steps at predetermined user selected sites. In another aspect, the invention provides template-free enzymatic synthesis with proofreading, wherein completed polynucleotides at predetermined reaction sites are sequenced using a sequencing by synthesis technique, particularly employing electrochemically labile blocking groups.

The invention discloses a report checking method capable of automatically feeding back a checking result based on a snapmake language. The method specifically comprises the following steps: step 1, file preparation: preparing a question settlement report and an analysis confirmation sheet excel table; 2, performing report basic information checking, quality control data checking, intra-group sample difference checking, report sample number and display sequence checking, report integrity checking and / or report picture checking in parallel and / or in series on the basis of the question settlement report obtained in the step 1 and an analysis confirmation single excel table; and step 3, generating a webpage version checking report according to one or more pieces of checking log information obtained in the step 2, and automatically sending feedback through a mail. The invention further discloses a system and application for implementing the report checking method, and the system and the application have wide application value.

The invention discloses a compression and decompression method based on generic genome expression, and relates to the technical field of compression and decompression of DNA next-generation sequencing data, in particular to the compression and decompression method based on generic genome expression. The method aims at solving the problems that in the prior art, the capacity of processing population genetic diversity is insufficient, original sequencing quality information cannot be effectively restored during decompression, and memory occupation is too high during large-scale data processing. Obtaining a to-be-compressed sequencing sequence data file, a reference genome sequence and a thousand-person genome variation sample; obtaining a haplotype list, a variation list and a haplotype offset list corresponding to each window block; storing the window number, the haplotype number, the haplotype offset, the head and tail unmatched sequences, the current sequence name and the quality score character string into a single compression block; carrying out binding storage; completing the compression processing of the mass fraction; and obtaining each to-be-compressed sequencing sequence based on the result of the compressed part.

The present invention relates to the field of protein engineering, and specifically relates to a Morchella esculenta peptide and the use thereof. By means of comprehensively applying bioinformatic methods such as virtual enzymolysis, activity prediction, physicochemical property and safety evaluation, and molecular docking, one Morchella esculenta peptide having the potential effects of "inhibiting oxidation + skin whitening" is screened from Morchella esculenta, which peptide has a sequence of WWVCAK. In-vitro chemical experiments verify that WWVCAK is the most effective antioxidant and tyrosinase-inhibitory peptide. Therefore, WWVCAK can exert the effects of inhibting oxidation and skin whitening via multiple targets, multiple functions and multiple pathways. WWVCAK is expected to be developed and used in cosmetics as a functional skin-care ingredient with the twin effects of "inhibiting oxidation + skin whitening".

Example systems and methods for using nested error correction codes for DNA data storage are described. A data unit may be encoded in a set of oligos. Using an error correction code, such as an LDPC code, a codeword may be determined for the data unit that is a multiple of the data payload capacity of each oligo. The codeword may be divided among the set of oligos, along with corresponding redundancy data. Any number of additional levels of nested error correction codes may be implemented by aggregating sets of smaller codewords into larger codewords and storing the corresponding redundancy data in the set of oligos. Each nested level may be aggregated from the set of oligos and decoded using the corresponding error correction code matrix and set of redundancy data as needed, such as in response to failure to decode codewords at a lower level.

The invention belongs to the technical field of biomedical engineering, and discloses a multiple biomarker detection system for diagnosis and classification of hepatic failure acute kidney injury, comprising a biomarker library construction module for obtaining historical hepatic failure acute kidney injury data to construct a biomarker library; the historical hepatic failure acute kidney injury data comprises biomarker data, pathological image data and patient clinical data; the data processing module is used for preprocessing the acquired biomarker data, pathological image data and patient clinical data to obtain a biomarker feature data set, a pathological image feature data set and a clinical feature data set; the acute kidney injury diagnosis module is used for fusing the biomarker feature data set, the pathological image feature data set and the clinical feature data set to obtain a comprehensive feature data set; inputting the comprehensive feature data set into a trained acute kidney injury diagnosis model, and predicting to obtain acute kidney injury type data; and the diagnosis accuracy is improved.

A bioengineering method which comprises introducing an inert nucleic acid cassette into a biological entity without introducing or modifying characteristics or traits in the biological entity. The method comprises receiving or providing a sample comprising the biological entity having a nucleic acid sequence; selecting an integration site in the nucleic acid sequence for inserting the inert nucleic acid cassette; designing the inert cassette with optimized primer sequences, optimized probe sequences, optimized stop codons and disrupted start codons, and inserting the inert nucleic acid cassette into the biological entity at the integration site; and validating that no characteristics have been added or modified in the biological entity.

The invention provides a cross-domain shared biological information metadata integration and management platform, and belongs to the technical field of bioinformatics. Comprising a metadata acquisition module used for supporting uploading of various metadata file formats, recording data change history and providing field preview and condition prompt; the metadata standardization and semantic mapping module is used for realizing field semantic analysis, standardized mapping and user-defined mapping management through a built-in biological ontology library; the universal metadata model building module is used for providing a dual-interface definition metadata structure template and realizing model version control and field verification; the authority control and sharing mechanism module is used for setting a data visibility authority and distributing a metadata unique reference identifier; the advanced retrieval and semantic search module is used for supporting condition combination retrieval and natural language semantic association retrieval; and a database. According to the method, standardized integration, safe sharing and semantic retrieval of the multi-source heterogeneous metadata are realized, the cross-laboratory cooperation efficiency is improved, and the scientific research cost is reduced.

The application discloses an intelligent agent-oriented biological information analysis method, comprising the following steps: a biological information tool register is established in advance, wherein the tool register comprises input data format, execution condition and output data format; the method further comprises the following steps: receiving a biological information task description, comparing the data format of the biological information according to the biological information tool register; in response to the comparison result of the data format, performing data standardization to execute the biological information task, and determining the task score confidence according to the execution condition; the input and output formats and the execution condition of the biological information tool are unified through the structured register, so that the intelligent agent can query and call the tool without understanding the internal implementation of the tool; the data format is automatically compared and pre-diagnosed, and when the data format is not matched, the standardization is completed by the self-adaptive conversion tool, so that the process interruption is eliminated; the confidence is captured according to the execution condition, the analysis result is outputted with the confidence index, and the result confidence is improved.

The invention discloses a multi-omics-based coronary heart disease hierarchical diagnosis system and application thereof, and relates to application of personal information in a system for diagnosing whether a subject has no coronary heart disease (NCA) or suffers from the coronary heart disease, and the coronary heart disease comprises stable coronary heart disease (sCAD) and acute coronary syndrome (ACS). The multi-dimensional feature set is constructed by integrating clinical, microbial and metabolic features, potential information provided by data of different dimensions is fully utilized, and the diagnostic performance of the model is remarkably improved; through a Boruta algorithm and an SHAP framework, a series of new metabolite and microbial biomarker information is found, and the method can be used for accurately distinguishing the coronary heart disease and the stable coronary heart disease acute coronary syndrome.

The invention discloses a multi-channel extensible automatic sample loading system for DNA storage and calculation and a control method. The system comprises a gas path control device, a multi-channel sample introduction device, a liquid flow control device, a multi-liquid-path liquid collection device, a micro-fluidic chip and an upper computer, operation control over the whole system is provided through the upper computer, a user can adjust the sample injection sequence and the reaction time of each channel, the liquid flow and the gas flow of each channel are monitored and adjusted in real time in an experiment, and multi-channel and high-precision automatic sample injection is achieved. According to the invention, accurate injection and automatic control of samples are realized, the efficiency and precision of sample treatment are greatly improved, and high automation, high-precision sample injection and multi-channel low cross contamination control capability are realized; the expandability is high, and modular expansion to hundreds of channels or even hundreds of channels is supported; meanwhile, the method is compatible with various application scenes, and is suitable for the fields of high-throughput DNA calculation, DNA information storage, biomedical detection and the like.

The present invention discloses an information storage method based on DNA coding. The method comprises the following steps: converting digital information to be stored into a quaternary code, and converting the quaternary code into a DNA sequence consisting of adenine A, cytosine C, guanine G, and thymine T according to a preset mapping rule, and using the chemical modification state of the nucleotide pairs to represent an additional information dimension; inserting error detection and correction codes at every predetermined number of base positions in the DNA sequence, dividing the encoded DNA sequence into multiple fragments of 100-150 bp in length, and adding specific recognition sequences and index markers at both ends of each fragment; utilizing a reversibly thermoresponsive DNA nanostructure as a carrier, selectively binding the DNA fragments to the carrier, and realizing hierarchical storage and rapid retrieval of information through a temperature gradient control system; the present invention can significantly improve the information density and lifespan of DNA storage, and provides a new technical path for large-scale, long-term, and secure molecular information storage.

A method for constructing a database for discrimination of microorganisms according to the present disclosure includes: a step (S12) for acquiring genome data of two kinds of microorganisms; a step (S14) for predicting a group of proteins produced by each of the two kinds of microorganisms; a step (S16) for producing a list of mass-charge ratios of each of the two kinds of microorganisms; a step (S20) for calculating the degree of similarity between the lists of the mass charge ratios; a step (S32) for generating information that includes the fact that the two kinds of microorganisms cannot be discriminated by MALDI-MS when the degree of similarity is equal to or larger than a predetermined value; and a step (S36) for outputting the information.

This application discloses a method, apparatus, device, and product for constructing a multidimensional knowledge graph, applicable to the field of data processing technology. The method includes: acquiring at least two biomedical databases, wherein the biomedical databases store different entities and entity relationships connecting the different entities; standardizing similar entities in the at least two biomedical databases to obtain at least two standardized entities; reconstructing entity relationships between different standardized entities based on the entity relationships between different entities in the at least two biomedical databases; and constructing the multidimensional knowledge graph based on the at least two standardized entities and the entity relationships between different standardized entities. This method can construct a multidimensional knowledge graph, primarily based on gene-related entities, by integrating databases.

Systems and methods of the present disclosure are provided for detecting the presence of a pathogen or living organism within a sample. FT-IR is used to determine an absorption profile of the sample, which is used to determine the presence of the pathogen in the sample and determine a concentration of the pathogen in the sample. The systems and methods are further configured for detection and treatment of antibiotic resistance genes within the pathogen detected, using the absorption profile of the sample and the absorption profile of the pathogen.

This application relates to methods for operating a multi-modal sensor device and associated apparatus. The invention provides a BMD that has multiple device modes depending on the operating conditions of the device, such as motion intensity, device placement, and / or activity type, which are associated with various data processing algorithms. In some embodiments, the BMD is implemented as a wrist-worn or arm-worn device. In some embodiments, methods are provided for tracking physiological metrics using the BMD. In some embodiments, the process and the BMD apply time-domain analysis to data provided by the sensors of the BMD when the data has high signal (e.g., high signal-to-noise ratio), and apply frequency-domain analysis to the data when the data has low signal, which facilitates improved accuracy and speed of biometric data.

A computer-implemented federated studies system and method are disclosed. The system includes: a predefined common data model associated with a study; a set of sites of origin, each associated with a set of input devices for acquiring study data from subjects and a study data device. Each study data device includes: a database for storing study data derived from input devices; a data model translator for translating study data to a common data model format; a common model database for storing, in the data model, individual participant values derived from study data; a study compute module for determining site aggregate values from individual participant values; and an aggregate database for storing site aggregate values. A site of analysis is associated with a study analysis device that includes: an analysis compute module for processing site aggregate values received from sites of origin; and a reporting module for generating study reports.

The invention discloses a colon cancer diagnostic marker screening method and system based on transcriptome data, and belongs to the technical field of biological information, and the method comprises the steps of data preparation, pathological hierarchical modeling, diagnostic marker screening and screening report generation. According to the method, pathological hierarchical modeling based on dynamic discrimination and double-layer feature fusion is adopted, on the basis of comprehensively considering gene expression and pathological morphology information, pathological subtypes of colon cancer samples are adaptively recognized, stable and representative subtype features are obtained, and therefore the accuracy and biological representativeness of diagnostic marker screening are improved; diagnostic marker screening based on pathological subtype difference analysis is adopted, and on the premise of considering pathological subtype characteristics, a stable and reliable diagnostic marker set with remarkable expression difference is screened in a targeted manner, so that the biological representativeness, screening robustness and diagnostic specificity of markers are improved.

To provide a technique for easily and accurately registering information for identifying a program used for processing each set of analytic data in a device for processing analytic data acquired by multiple types of analysis devices.SOLUTION: Two or more types of processing modules and module information defining a character string corresponding to each of the two or more types of processing modules are stored in memory of a data management device 1. A processor of the data management device selects one processing module to be used for processing given analytic data from among the two or more types of processing modules on the basis of a character string included in a file name of the given analytic data and the module information for the given analytic data.SELECTED DRAWING: Figure 1

The present disclosure provides biomarker screening model training method and device, method and device, network, equipment and medium, and relates to the technical field of image processing. The implementation scheme of the present disclosure is: a heterogeneous graph construction module, configured to convert an obtained target data set into a heterogeneous graph structure; a double-flow graph convolution network module, wherein a protein interaction flow network is configured to output a first graph-level feature based on a first adjacency matrix; a gene regulation flow network is configured to output a second graph-level feature based on a second adjacency matrix; an attention fusion classification module is configured to weight and fuse the first graph-level feature and the second graph-level feature, and input the fused feature into a classifier to obtain a prediction probability value for a target disease category; and an explainable attribution module is configured to integrate a gradient along a path from a baseline input to an actual input, quantify a contribution score of each protein node feature in the heterogeneous graph structure to the prediction probability value, and output a candidate biomarker combination according to the contribution score.

The application provides a protein virtual screening method, device and equipment and a storage medium, and belongs to the field of drug discovery. The method comprises the following steps: obtaining a training sample set, wherein the training sample set comprises source data and sample data corresponding to the source data; performing unsupervised pre-training on a Transformer model by taking the source data as input and the sample data as verification, and generating one-dimensional or multi-dimensional symmetric matrices for protein sequences and ligand sequences respectively; coupling the two matrices of the protein sequences and the ligand sequences into a multi-dimensional symmetric matrix, and taking the multi-dimensional symmetric matrix as the input of a hidden layer of a BiLSTM network model; fitting experimental measurement classification and regression values of the interaction between proteins and small molecules by using the BiLSTM network model to obtain a trained screening model; and performing prediction on different protein prediction tasks by using the screening model and outputting a prediction result. According to the processing scheme, the interaction relationship between proteins and small molecule drugs can be efficiently, quickly and accurately predicted.