39557 results about "Bioinformatics" patented technology

The technology described herein relates to systems, methods, and computer storage media, among other things, for providing search query intent specificity. Embodiments may include identifying a search query performed using a search engine and generating a query vector for the search query by aggregating search result embeddings (e.g., item listing vectors) of search results from the search query. Further, in some embodiments, similarities (e.g., cosine similarities) between the query vector and the item listing vectors can be determined. As such, an intent specificity of the search query can be determined. Further, in some embodiments, the intent specificity can be used to train an intent specificity machine learning model for generating intent specificity scores for other search queries. Based on the intent specificity scores determined using the one or more trained intent specificity machine learning models, determinations can be made with respect to precision and recall, etc.

The method can include: recording a neural state, determining a latent array, and determining an output based on the latent array. In variants, the method can function to enable a subject to use neural signals to navigate within a high-dimensional concept space to control an output (e.g., image generation, motor control, communication, etc.).

Disclosed herein are methods of amplifying an analyte in a biological sample using a bridging oligonucleotide that hybridizes to a captured analyte. The methods disclosed herein include steps of (a) contacting a biological sample with a substrate having capture probes comprising a capture domain and a spatial barcode; (b) hybridizing the analyte to the capture domain; and (c) contacting the analyte to a bridging oligonucleotide comprising (i) a capture-probe-binding sequence, and (ii) an analyte-binding sequence; (d) extending the bridging oligonucleotide; and (e) determining (i) all or a part of the sequence of the analyte, or a complement thereof, and (ii) the spatial barcode, or a complement thereof, and using the determined sequence of (i) and (ii) to determine the location of the analyte in the biological sample.

Provided herein are methods, kits, and compositions for determining the spatial location of non-coding RNA, such as siRNA and / or miRNA in a biological sample.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

The present disclosure provides methods and compositions for detecting and spatially locating analyte interactions and gene expression in a biological sample. For example, provided herein are methods of determining a location of at least one analyte in a biological sample using analyte-binding moieties, proximity ligation, and an array including capture probes.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

Provided herein are methods and compositions disclosing an approach that combines single nuclear RNA-seq (snRNA-seq) with spatial transcriptomics. The methods include processing and analyzing multiple analytes in a biological sample, and utilizes multiple substrates, one having a spatial array having a plurality of capture probes, each having a capture domain and a spatial barcode. The methods can be used to detect location of both nucleic acid and protein analytes. The methods also include isolating cells and / or nuclei from a sample and determining analyte expression in the isolated cells and / or nuclei.

Provided herein are methods of determining a location of a biological analyte in a biological sample.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

Provided herein are methods for preparing biological samples for spatial proteomic analysis, methods of determining a location of a protein analyte in a biological sample, and methods of determining a location of a protein analyte and a nucleic acid analyte in a biological sample.

The present disclosure features methods, compositions, and kits for spatially barcoded, reusable master oligonucleotide probes.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

Provided herein are methods of detecting an analyte of interest to interrogate spatial gene expression in a sample using RNA-templated ligation.

Provided herein are methods, compositions, and kits for the spatial detection of analytes using ligation-based capture assays.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

The invention relates to the technical field of medical artificial intelligence and knowledge graph construction, in particular to a rare disease knowledge graph construction method based on modal injection and multi-modal fusion. Comprising the following steps: S1, collecting multi-modal medical information including texts, images and genes; s2, standardization processing is carried out, and a three-layer metadata structure is constructed; s3, complementing missing modal data, and performing feature extraction and unified dimension conversion on the modal data to realize representation alignment in a shared semantic space; s4, performing multi-level semantic fusion to obtain a unified fusion semantic vector; and S5, constructing a double-layer structure system rare disease knowledge graph comprising an ontology layer and an instance layer. According to the method, multi-modal medical information of texts, images and genes is selected to construct the knowledge graph of the rare disease, the application range, coverage and accuracy of the knowledge graph are improved, correspondence adaptation of rare cases during clinical diagnosis and treatment of the rare disease can be achieved, and the method has high recognition capacity.

The invention discloses a ligand information generation model training method and device and a ligand information generation method and device, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring sample receptor information and sample ligand information, wherein the binding affinity between a ligand described by the sample ligand information and a receptor described by the sample receptor information is not less than a set affinity; denoising the reference noise data based on the sample receptor information through a to-be-trained neural network model to obtain predicted ligand information; determining a first loss for characterizing a difference between the sample ligand information and the predicted ligand information; and training the neural network model based on the first loss to obtain a ligand information generation model. The reference ligand information can be generated based on the reference receptor information through the ligand information generation model, and the binding affinity between the ligand described by the reference ligand information and the receptor described by the reference receptor information is high.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

The present disclosure relates to a multimodal computing-based early intelligent graded screening system for a brain disease. The system comprises: a multimodal data acquisition unit, configured to acquire multimodal data of a target patient under a specified screening grade to form a screening data set; a multimodal feature generation, completion, fusion and calculation unit, configured to generate and complete feature data of modal features in the screening data set to obtain complete modal features, and extract pathological features for calculation to obtain a first screening result; a knowledge-based intelligent screening unit, configured to encode the feature data of the modal features in the screening data set into corresponding graph structure data features, use a multimodal association graph optimized by expert knowledge to match the graph structure data features to obtain knowledge-based association features, and obtain a second screening result on the basis of the knowledge-based association features; and an intelligent graded screening unit, configured to carry out weighted calculation on the first screening result and the second screening result to obtain a final screening result. The present disclosure achieves accurate early screening of brain diseases of patients.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

The method can include: recording a neural state, determining a latent array, and determining an output based on the latent array. In variants, the method can function to enable a subject to use neural signals to navigate within a high-dimensional concept space to control an output (e.g., image generation, motor control, communication, etc.).

Provided herein are methods of identifying genetic variants in biological samples. In particular, the present disclosure uses spatial transcriptomic templated ligation methods and compositions to identify the presence or absence, and the location of genetic variants in the transcriptome or genome of a biological sample.

Provided herein are methods, compositions, and systems for improved in situ detection of analytes and spatial analysis using, e.g., a sequencing readout.

The present disclosure relates to materials and methods for spatially analyzing nucleic acids that have been fragmented with a transposase enzyme, alone or in combination with other types of analytes.

The invention relates to the field of medical informatization. The invention discloses a thyroid cancer electronic medical record system based on multi-modal data fusion. The thyroid cancer electronic medical record system comprises a multi-modal data acquisition module which acquires patient texts, ultrasonic images, genes, biochemical indexes and clinical data and performs standardized calibration to generate standard data; the multi-modal feature extraction module extracts semantic, structure, mutation, change and fluctuation features of each standard data through multiple technologies; the single-mode prediction model construction module constructs single-mode prediction models of texts, images and the like based on the features and outputs results; and the multi-modal fusion prediction module fuses the single-modal model based on the deep learning framework to output a multi-modal fusion prediction result. According to the invention, multi-modal data are integrated, and the accuracy and comprehensiveness of thyroid cancer diagnosis are improved. The system ensures consistency through standardized data processing, and assists doctors to accurately judge pathological types, recommend therapeutic schedules and evaluate prognosis by means of a multi-modal feature extraction and fusion mechanism.