31results about "Recognition of DNA microarray pattern" patented technology

Image data analysis, and particularly identifying cluster or polony locations for performing base-calling in a digital image of a flow cell during DNA sequencing is described. A method may include generating a first plurality of flow cell images of a cellular sample immobilized on a support by conducting one or more cycles of sequencing reactions. The cellular sample may include a plurality of concatemer molecules therewithin. For the first plurality of flow cell image, pixel intensities, and a respective color purity of each of the pixel intensities may be determined. A base calling template may include base calling locations based on the pixel intensities and the respective color purity of the pixel intensities. The base calling template may be for registering a second plurality of flow cell images of the support in one or more subsequent cycles of the one or more cycles.

The application relates to the field of protein deconvolution analysis, in particular to a mass spectrum analysis method and device and an intelligent terminal. The mass spectrum analysis method comprises the following steps: obtaining a target spectrum, wherein the target spectrum is used for reflecting mass spectrum data of a protein peptide segment; determining a spectrum feature of the target spectrum based on a mass-to-charge ratio of the target spectrum; inputting the spectrum feature of the target spectrum into a preset deconvolution model to obtain an analysis category of the target spectrum, wherein the analysis category is used for reflecting a peptide sequence corresponding to the target spectrum. The mass-to-charge ratio of the target spectrum is used to obtain the spectrum feature, and the spectrum feature is input into the deconvolution model, and the analysis category is obtained through the deconvolution model. The application has the characteristics that the peptide sequence of the protein corresponding to the target spectrum can be effectively, accurately and quickly analyzed.

The technology disclosed relates to equalizer-based intensity correction for base calling. In particular, the technology disclosed relates to accessing an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters, selecting a lookup table that contains pixel coefficients that are configured to increase a signal-to-noise ratio, applying the pixel coefficients to intensity values of the pixels in the image to produce an output, and base calling the target cluster based on the output.

The present application provides a data processing method and apparatus, a device, and a storage medium, which can be applied to the technical fields of artificial intelligence, bioengineering and the like. The method comprises: acquiring data to be processed, and parsing said data to obtain spatial position information and first feature information of each object in N objects; converting said data into a first image on the basis of the spatial position information and the first feature information of each object; from the first image, extracting second feature information of each object in the N objects; and performing preset processing on the second feature information of each object in the N objects to obtain a processing result of said data. According to the method, data to be processed is converted into a first image, the first image is subjected to feature extraction to obtain second feature information of N objects, and spatial position information is encoded into features; the whole data processing process is simple, a small quantity of computing resources are occupied, and the data processing efficiency is high.

The present invention provides a method for detecting a chromosome copy-number variant (CNV). The method comprises: performing PCA noise reduction and CNV analysis on sequencing data of a sample to be detected, so as to detect whether said sample contains a CNV and / or determine a CNV source, wherein the PCA noise reduction is performed by comparing the sequencing data of said sample with a reference data set, and the reference data set is a principal component feature which represents noise and is obtained after PCA learning is performed on a predetermined sample. According to the method, a CNV can be accurately detected, and the occurrence source of the CNV can be determined, so that false positive or false negative results caused by a maternal CNV in a sample to be detected are effectively avoided, and false detection or missing detection of congenital defects of fetuses is prevented.

The present disclosure describes systems, non-transitory computer-readable media, and methods for determining adjusted locations of clusters of oligonucleotides based on a phase difference between band-edge spectral regions of a nucleotide-sample-slide region image. For example, the disclosed systems (i) identify a pair of band-edge spectral regions from a spatial frequency band in an oligonucleotide-cluster image and (ii) determine a phase difference between the pair of band-edge spectral regions. Based on the phase difference, the disclosed systems generate a location error in at least one direction for predicted locations of the oligonucleotide clusters. Based on the location error, the disclosed systems determine adjusted locations of the oligonucleotide-clusters within the nucleotide-sample-slide region.

The disclosed technology attenuates spatial crosstalk from sequencing images used for base calling. Specifically, the disclosed technology accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional neighboring clusters. These pixels include a center pixel that contains a center of the target cluster. Each of these pixels can be divided into a plurality of subpixels. From a particular subpixel, among the plurality of subpixels of the center pixel that contains the center of the target cluster, the disclosed technology selects a subpixel lookup table corresponding to the particular subpixel from a library of subpixel lookup tables. The selected subpixel lookup table contains pixel coefficients configured to maximize a signal-to-noise ratio. The disclosed technology multiplies these pixel coefficients element-wise with the pixels and determines a weighted sum.

Image data analysis, particularly identifying cluster locations for performing base-calling in a digital flow cell image during DNA sequencing, is described. Each nucleic acid template molecule immobilized on a support may include an insert sequence and a sample index sequence. The sample index sequence may include a k-mer sequence. A sequencing system may conduct k cycles of sequencing reactions of the k-mer sequence before conducting one or more cycles of the insert sequence sequencing reactions and generate a first plurality of flow cell images. Pixel intensities may be determined for pixels of the first plurality of flow cell images. A base calling template may be determined and include base calling locations based on the pixel intensities and respective color purities of the pixel intensities. The base calling template may register a second plurality of flow cell images of the support in one or more cycles subsequent to the k cycles.

The application discloses a kind of stomach cancer HER2 state prediction model training, prediction method and system, wherein, training method includes: obtaining sample image set, the sample image set includes first dyeing image and second dyeing image;Second dyeing image in the sample image set is marked with state, and image label is obtained;The sample image set is pathologically annotated, and training sample set is obtained;The training sample set and the image label are input into untrained stomach cancer HER2 state prediction model and are trained, and the stomach cancer HER2 state prediction model of training completion is obtained.The embodiment of the application can improve the accuracy of stomach cancer HER2 state prediction model, and can be widely applied in artificial intelligence technical field.

A computer-implemented method comprises: determining coefficients corresponding to a section of a flow cell; accessing an image depicting the section of the flow cell and intensity emissions from a target cluster of concatemers; and generating a base call for the target cluster of concatemers by applying the coefficients to the intensity emissions for the target cluster of concatemers.

The present invention relates to a method for establishing a correlation between sizes of genetic material contained in virus, virus-like particles (VLPs) or bacteriophages and the measured particle interior intensities of the particles using hydrated state imaging to quantitatively describe, separate and classify the particle populations. The method further comprises the step of graphically displaying the distribution of the particle interior intensities for each reference sample relative to sizes of the genetic material in each reference sample.

The technology disclosed accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The technology disclosed selects, from a bank of lookup tables, a lookup table that contains pixel coefficients that are configured to increase a signal-to-noise ratio. The technology disclosed applies the pixel coefficients to the pixels having intensity values to produce an output, and base calls the target cluster based on the output.

A mutation detection apparatus includes a memory configured to store software for implementing a neural network and a processor configured to detect a mutation by executing the software, wherein the processor is configured to generate first genome data extracted from a target tissue and second genome data extracted from a normal tissue, extract image data by preprocessing the first genome data and the second genome data, and detect a mutation of the target tissue on the basis of the image data through the neural network trained to correct a sequencing platform-specific false positive.

Methods and systems for image analysis are provided, and in particular for identifying a set of base-calling locations in a flow cell for DNA sequencing. These include capturing flow cell images after each sequencing step performed on the flow cell, and identifying candidate cluster centers in at least one of the flow cell images. Intensities are determined for each candidate cluster center in a set of flow cell images. Purities are determined for each candidate cluster center based on the intensities. Each candidate cluster center with a purity greater than the purity of the surrounding candidate cluster centers within a distance threshold is added to a template set of base-calling locations.

Methods and systems for determining a plurality of sequences of nucleic acid (e.g., DNA) molecules in a sequencing-by-synthesis process are provided. In one embodiment, the method comprises obtaining images of fluorescent signals obtained in a plurality of synthesis cycles. The images of fluorescent signals are associated with a plurality of different fluorescence channels. The method further comprises preprocessing the images of fluorescent signals to obtain processed images. Based on a set of the processed images, the method further comprises detecting center positions of clusters of the fluorescent signals using a trained convolutional neural network (CNN) and extracting, based on the center positions of the clusters of fluorescent signals, features from the set of the processed images to generate feature embedding vectors. The method further comprises determining, in parallel, the plurality of sequences of DNA molecules using the extracted features based on a trained attention-based neural network.

Methods for utilizing a nucleic acid-based multilevel perceptron are provided.

A method for quantifying labels on a substrate is performed by an electronic device with one or more processors and memory. The method includes obtaining digital data corresponding to a multi-dimensional measurement over the substrate; identifying a first set of sub-portions of the digital data; and, for a respective sub-portion of the first set of sub-portions of the digital data: increasing a quantity of labels, and subtracting a reference signal distribution from the respective sub-portion to obtain subtracted sub-portion data. The method also includes obtaining subtracted digital data. The subtracted digital data includes the subtracted sub-portion data for the respective sub-portion. The method further includes identifying a second set of one or more sub-portions of the subtracted digital data; and, for a respective sub-portion of the second set of one or more sub-portions of the subtracted digital data, increasing a quantity of labels.

The technology disclosed attenuates spatial crosstalk from sequencing images for base calling. In particular, the technology disclosed accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The pixels include a center pixel that contains a center of the target cluster. Each pixel in the pixels is divisible into a plurality of subpixels. Depending upon a particular subpixel, in a plurality of subpixels of the center pixel, which contains the center of the target cluster, the technology disclosed selects, from a bank of subpixel lookup tables, a subpixel lookup table that corresponds to the particular subpixel. The selected subpixel lookup table contains pixel coefficients that are configured to maximizes a signal-to-noise ratio. The technology disclosed element-wise multiplies the pixel coefficients with the pixels and determines a weighted sum.

System and methods in this disclosure identify leakage from one partition to surrounding partitions. Detecting leakage may include input data describing the location of the partition, the fluorescence intensity, and whether the partition is positive for an analyte. A machine learning model may be trained on an extensive input data set to identify partitions that have leakage or a high probability of leakage. In some embodiments, features used in the machine learning model include values that describe a neighborhood around the partition and not merely the partition itself.

To attenuate spatial crosstalk from sequencing images for base calling.SOLUTION: The disclosed technology accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The pixels include a center pixel that contains a center of the target cluster. Each pixel in the pixels is divisible into a plurality of subpixels. Depending upon a particular subpixel, in a plurality of subpixels of the center pixel which contains the center of the target cluster, the disclosed technology selects, from a bank of subpixel lookup tables, a subpixel lookup table that corresponds to the particular subpixel. The selected subpixel lookup table contains pixel coefficients that are configured to maximize a signal-to-noise ratio. The disclosed technology element-wise multiplies the pixel coefficients with the pixels and determines a weighted sum.SELECTED DRAWING: Figure 1B

The technology disclosed relates to equalizer-based intensity correction for base calling. In particular, the technology disclosed relates to accessing an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters, selecting a lookup table that contains pixel coefficients that are configured to increase a signal-to-noise ratio, applying the pixel coefficients to intensity values of the pixels in the image to produce an output, and base calling the target cluster based on the output.

A computer-implemented method for determining an output signal characterizing a first classification of an input image into a class from a plurality of classes. The output signal further characterizes a second classification of a robustness of the first classification against an attack with an adversarial patch.

This disclosure relates to sensing the movement of DNA rolling motors comprising microparticles or rods on transduction material in the presence of viruses, microbes, or other analytes for diagnostic testing. In certain embodiments, the presence of viral particles, other target microbial biomolecules, or analytes stall the motor by specifically binding to aptamers crosslinking the analytes to the particles, rods, or surface of the transduction material. It is contemplated that microparticles or other rolling motors move along a surface whereby an aptamer targets an analyte, e.g., viral SARS-CoV-2, and acts to inhibit, reduce, or restrict the speed, acceleration, or area of movement on the surface indicating the presence of the analyte in the sample.

A base calling method and system, a gene sequencer and a storage medium. The base calling method comprises the following steps: acquiring a first image of a biochip in a red light channel and a second image of the biochip in a green light channel (S1); performing base grouping according to the first image and the second image, and preliminarily identifying the base category of each group (S2); when the number of the base categories of all the groups is at least two, adjusting the brightness value of the first image and the brightness value of the second image according to the base categories of all the groups (S3); respectively performing normalization processing on the first image and the second image (S4); and performing base grouping according to the normalized first image and the normalized second image, and identifying the base category of each group again (S5). The base calling method can accurately identify base categories for data to be sequenced in which some base categories are missing, so that the accuracy of gene sequencing can be improved.

The application discloses a center positioning method and device of a fluorescent cluster, a terminal device and a computer readable storage medium. A preset clustering algorithm is used to obtain a brightness segmentation threshold of a sub-image of a fluorescent image. The sub-image is subjected to threshold segmentation according to the brightness segmentation threshold to obtain a fluorescent cluster segmentation image corresponding to the fluorescent image. A fluorescent cluster template is determined according to the area size of each fluorescent cluster in the fluorescent cluster segmentation image. The center of the fluorescent cluster is positioned according to the brightness distribution of the fluorescent cluster in the fluorescent cluster template and the maximum brightness point in the fluorescent cluster to obtain a cluster center. The application solves the technical problem that the conventional fluorescent cluster center positioning method is prone to failure in the case of fluorescent cluster adhesion, thereby failing to accurately position the center of the fluorescent cluster.

The technology disclosed extracts intensities from sequencing images for base calling target clusters and attenuates spatial crosstalk from neighboring clusters. The technology disclosed accesses a particular section from a plurality of sections of an image output by a sensor, the particular section of the image including at least one pixel depicting intensity emission values from a target cluster and neighboring clusters located across the sensor, and convolves the particular section of the image with a corresponding convolution kernel in a plurality of convolution kernels, to generate a feature map comprising a plurality of feature values. The technology disclosed further assigns a corresponding feature value to the target cluster based on feature values in the plurality of feature values adjoining a center of the target cluster, and processes the corresponding feature value assigned to the target cluster, to base call the target cluster.

A computer-implemented method comprises: determining coefficients corresponding to a section of a flow cell; accessing an image depicting the section of the flow cell and intensity emissions from a target cluster of concatemers; and generating a base call for the target cluster of concatemers by applying the coefficients to the intensity emissions for the target cluster of concatemers.

A computer implementation method for determining an output signal (y) that characterizes a first classification (c) of an input image (x) as a category from a plurality of categories, wherein the output signal (y) further characterizes a second classification (r) of the robustness of the first classification (c) against attacks with adversarial patches, wherein determining the output signal (y) comprises the following steps: - determining a plurality of first score maps (M), wherein the first score maps correspond to categories from the plurality of categories and include a plurality of region classifications, wherein each region classification characterizes whether a region belongs to the category for a region in a plurality of regions of the image; - determining a plurality of first category scores, wherein each first category score from the plurality of first category scores corresponds to a category from the plurality of categories, and is determined by aggregating the region classifications that characterize the classification as the category from the first score maps corresponding to the categories; - determining a second category score, wherein the second category score is determined when adversarial patches are applied to the input image to change the corresponding category. - The minimum category score obtainable in the case of region classification of the first score map corresponding to the first category with the maximum first category score; - Determine a plurality of third category scores, wherein the third category scores correspond to categories different from the first category, and are the maximum category scores obtainable in the case of region classification of the first score map of the first category when adversarial patches are applied to the input image (x) to change the category; - If the second category score is greater than or equal to all third category scores, determine the output signal (y) such that it characterizes the first category (c) of the input image based on the plurality of first category scores, and it characterizes the second category (r) of the first category as robust to the adversarial patch; - If the second category score is less than at least one third category score, determine the output signal (y) such that it characterizes the first category (c) of the input image based on the plurality of first category scores, and it characterizes the second category (r) of the first category as not robust to the adversarial patch.

To attenuate spatial crosstalk from sequencing images for base calling.SOLUTION: The disclosed technology accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The pixels include a center pixel that contains a center of the target cluster. Each pixel in the pixels is divisible into a plurality of subpixels. Depending upon a particular subpixel, in a plurality of subpixels of the center pixel which contains the center of the target cluster, the disclosed technology selects, from a bank of subpixel lookup tables, a subpixel lookup table that corresponds to the particular subpixel. The selected subpixel lookup table contains pixel coefficients that are configured to maximize a signal-to-noise ratio. The disclosed technology element-wise multiplies the pixel coefficients with the pixels and determines a weighted sum.SELECTED DRAWING: Figure 1B

Direct targeted sequencing (DTS) methods and a hidden Markov model (HMV) can be used to call the copy number of a segment of interest within a region of interest. Described herein are methods for calling a copy number variant or a copy number variant abnormality using an HMM, and methods for determining a copy number based on a copy number likelihood model, in a test sequencing library that has be sequenced using DTS methods. Also described herein are methods for determining a copy number of a segment, including accounting for spurious capture probes that may arise from the DTS methods.