Patents Examined by Mary K Zeman
  • Patent number: 11996168
    Abstract: The present invention relates to genomic informatics and gene-expression profiling. Gene-expression profiles provide complex molecular fingerprints regarding the relative state of a cell or tissue. Similarities in gene-expression profiles between organic states provide molecular taxonomies, classification, and diagnostics. Similarities in gene-expression profiles resulting from various external perturbations reveal functional similarities between these perturbagens, of value in pathway and mechanism-of-action elucidation. Similarities in gene-expression profiles between organic and induced states may identify clinically-effective therapies. Systems and methods herein provide for the measurement of relative gene abundances, including unbiased selection of and construction of probes and targets designed and methods for using known properties of sparsity of measurements to reach gene abundances.
    Type: Grant
    Filed: October 27, 2016
    Date of Patent: May 28, 2024
    Assignees: The Broad Institute, Inc., Massachusetts Institute of Technology
    Inventors: Aviv Regev, Eric S. Lander, Brian Cleary, Le Cong
  • Patent number: 11988626
    Abstract: A biosensor system determines analyte concentration from an output signal generated from a light-identifiable species or a redox reaction of the analyte. The biosensor system compensates at least 50% of the total error in the output signal with a primary function and compensates a portion of the remaining error with a residual function. The amount of error compensation provided by the primary and residual functions may be adjusted with a weighing coefficient. The compensation method including a primary function and a residual function may be used to determine analyte concentrations having improved accuracy from output signals including components attributable to error.
    Type: Grant
    Filed: February 4, 2020
    Date of Patent: May 21, 2024
    Assignee: Ascensia Diabetes Care Holdings AG
    Inventors: Huan-Ping Wu, Bern Harrison, Eric Maurer
  • Patent number: 11970742
    Abstract: Methods are provided for diagnosing pregnancy-associated disorders, determining allelic ratios, determining maternal or fetal contributions to circulating transcripts, and/or identifying maternal or fetal markers using a sample from a pregnant female subject. Also provided is use of a gene for diagnosing a pregnancy-associated disorder in a pregnant female subject.
    Type: Grant
    Filed: January 23, 2019
    Date of Patent: April 30, 2024
    Assignee: The Chinese University of Hong Kong
    Inventors: Yuk-Ming Dennis Lo, Rossa Wai Kwun Chiu, Kwan Chee Chan, Peiyong Jiang, Bo Yin Tsui
  • Patent number: 11887696
    Abstract: Described herein are systems and methods that receive as input a DNA or RNA sequence, extract features, and apply layers of processing units to compute one ore more condition-specific cell variables, corresponding to cellular quantities measured under different conditions. The system may be applied to a sequence containing a genetic variant, and also to a corresponding reference sequence to determine how much the condition-specific cell variables change because of the variant. The change in the condition-specific cell variables are used to compute a score for how deleterious a variant is, to classify a variant's level of deleteriousness, to prioritize variants for subsequent processing, and to compare a test variant to variants of known deleteriousness.
    Type: Grant
    Filed: November 20, 2018
    Date of Patent: January 30, 2024
    Inventors: Brendan Frey, Michael K. K. Leung, Andrew Thomas Delong, Hui Yuan Xiong, Babak Alipanahi, Leo J. Lee, Hannes Bretschneider
  • Patent number: 11881311
    Abstract: In various embodiments, the present description relates to the use of factors related to survival. The methods, compositions and systems described herein may be used to determine factors affecting survival, assess survival risk based on factors related to survival and/or make suggestions to increase the likelihood of survival longer than otherwise predicted.
    Type: Grant
    Filed: February 7, 2018
    Date of Patent: January 23, 2024
    Assignee: BioAge Labs, Inc.
    Inventors: Kristen Patricia Fortney, Yonatan Nissan Donner, Eric Kim Morgen, Jonah Daniel Sinick, Andrew Jarai Ho
  • Patent number: 11823446
    Abstract: Digital imagery can help to quantify seasonal changes in desirable crop phenotypes that can be treated as quantitative traits. Because limitations in precise and functional phenotyping restrain genetic improvement in the post-genomic era, imagery-based phenomics could become the next breakthrough to accelerate genetic gains in field crops. Whereas many phenomic studies focus on exploratory analysis of spectral data without obvious interpretative value, we used field images to directly measure soybean canopy development from phenological stage V2 to R5. Over three years, we collected imagery using ground and aerial platforms of a large and diverse nested association panel comprising 5,555 lines. Genome-wide association analysis of canopy coverage across sampling dates detected a large quantitative trait locus on soybean (Glycine max, L. Merr.) chromosome 19. This QTL provided an increase in yield of 47.3 kg·ha?1.
    Type: Grant
    Filed: February 12, 2018
    Date of Patent: November 21, 2023
    Assignee: Purdue Research Foundation
    Inventors: Katherine Martin Rainey, Alencar Xavier, Keith Cherkauer, Anthony Hearst
  • Patent number: 11802314
    Abstract: Methods of deconvolving a feature profile of a physical system are provided herein. The present method may include: optimizing a regression between a) a feature profile of a first plurality of distinct components and b) a reference matrix of feature signatures for a second plurality of distinct components, wherein the feature profile is modeled as a linear combination of the reference matrix, and wherein the optimizing includes solving a set of regression coefficients of the regression, wherein the solution minimizes 1) a linear loss function and 2) an L2-norm penalty function; and estimating the fractional representation of one or more distinct components among the second plurality of distinct components present in the sample based on the set of regression coefficients. Systems and computer readable media for performing the subject methods are also provided.
    Type: Grant
    Filed: December 19, 2018
    Date of Patent: October 31, 2023
    Assignee: The Board of Trustees of the Leland Stanford Junior University
    Inventors: Aaron M. Newman, Arash Ash Alizadeh
  • Patent number: 11798650
    Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional neural network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.
    Type: Grant
    Filed: October 15, 2018
    Date of Patent: October 24, 2023
    Assignee: Illumina, Inc.
    Inventors: Laksshman Sundaram, Kai-How Farh, Hong Gao, Jeremy Francis McRae
  • Patent number: 11788142
    Abstract: The compositions and methods provided herein allow for identification of causative genetic biomarkers for a disease condition or drug response.
    Type: Grant
    Filed: July 6, 2018
    Date of Patent: October 17, 2023
    Assignee: POPULATION BIO, INC.
    Inventors: Eli Hatchwell, Peggy S. Eis
  • Patent number: 11788135
    Abstract: As described below, disclosed herein are methods of analyzing DNA methylation in cell-free DNA (cfDNA) and genomic DNA (gDNA) from sequencing data.
    Type: Grant
    Filed: August 4, 2017
    Date of Patent: October 17, 2023
    Inventors: Yaping Liu, Manolis Kellis, Viktor Adalsteinsson, Zhizhuo Zhang
  • Patent number: 11766182
    Abstract: Various examples of methods and systems are provided for real-time signal processing. In one example, a method for processing data to select a pattern includes receiving data via a sensor, evaluating the data including waveforms over a time domain, averaging the waveforms to obtain a mean waveform, selecting a pattern based on the mean waveform, and generating a notification regarding the selected pattern. The pattern can include a start time, a hold time, and an end time. In another example, a system includes one or more sensors that detect the data and a mobile platform that evaluates the data, averages the waveforms to obtain the mean waveform and selects a pattern based on the mean waveform. A user interface can be used to communicate the notification regarding the selected pattern. The patterns can include breathing patterns, which can be used to reduce stress in a subject being monitored by the sensor.
    Type: Grant
    Filed: June 6, 2016
    Date of Patent: September 26, 2023
    Assignee: The Arizona Board of Regents on Behalf of the University of Arizona
    Inventor: Wolfgang Fink
  • Patent number: 11749377
    Abstract: A method for predicting at least one fitness value of a protein is implemented on a computer and includes the following steps: encoding the amino acid sequence of the protein into a numerical sequence according to a protein database, the numerical sequence comprising a value for each amino acid of the sequence; calculating a protein spectrum according to the numerical sequence; and for each fitness: comparing the calculated protein spectrum with protein spectrum values of a predetermined database, said database containing protein spectrum values for different values of said fitness, predicting a value of said fitness according to the comparison step.
    Type: Grant
    Filed: April 14, 2016
    Date of Patent: September 5, 2023
    Assignee: PEACCEL
    Inventors: Nicolas Fontaine, Frédéric Cadet
  • Patent number: 11718869
    Abstract: A method and a kit for determining genome instability based on next generation sequencing (NGS) are disclosed. The new method is used to determine whether there is homologous recombination defect by calculating a comprehensive value of one or more of pathogenic germline and somatic mutations, such as SNV, indels, and CNVs, and Biallelic germline and somatic mutations, pathogenic mutational signature, copy number variation (CNV) in homologous recombination repair (HRR) gene, genomic structural variation and genome instability. The genomics DNA is interrupted and added with an A adapter; then corresponding polymerase chain reaction (PCR) is conducted, and Whole genome sequencing is performed; the hybrid capture is conducted with designed probes of HRR genes and SNPs, and a captured DNA library is subjected to amplification and library sequencing; and then professional bioinformatics software is used for evaluation to determine the homologous recombination deficiency (HRD) status.
    Type: Grant
    Filed: March 15, 2021
    Date of Patent: August 8, 2023
    Inventors: Fang Lv, Huiting Yan, Yaxi Zhang, Shiqi Zheng, Yiqian Liu, Jianing Yu, Hong Lv, Weizhi Chen, Shan Zheng, Ji He, Bo Du
  • Patent number: 11697605
    Abstract: A computer of a microbial community analysis system includes an input unit configured to input a plurality of data groups including information indicating a nucleotide sequence of a gene of each of a plurality of microorganisms included in activated sludge in which a water treatment is performed; a similarity calculating unit configured to calculate a similarity between data groups on the basis of the nucleotide sequences included in the input data groups, and a coordinates calculating unit configured to calculate coordinates in a multidimensional space of each of the data groups on the basis of the calculated similarity.
    Type: Grant
    Filed: March 30, 2016
    Date of Patent: July 11, 2023
    Assignee: Sumitomo Chemical Company, Limited
    Inventors: Hiroyuki Asako, Fumiyoshi Okazaki
  • Patent number: 11664092
    Abstract: Disclosed herein are biomarkers associated with a disease state such as lung cancer, and methods of discovering or using biomarkers. Also disclosed herein are classifiers built on biomarkers and methods of detecting the disease state in samples from subjects. The method may include obtaining a data set that includes protein information from a biofluid sample, and may involve using a classifier to identify the sample as indicative of a healthy state, a disease state, or a comorbidity.
    Type: Grant
    Filed: January 26, 2022
    Date of Patent: May 30, 2023
    Assignee: PrognomIQ, Inc.
    Inventors: John E. Blume, William C. Manning, Gregory Troiano, Asim Siddiqui, Philip Ma, Omid C. Farokhzad
  • Patent number: 11605446
    Abstract: The present disclosure provides methods and systems for determining and/or characterizing one or more haplotypes and/or phasing of haplotypes in a nucleic acid sample. In particular, the disclosure provides methods for determining a haplotype and/or phasing of haplotypes in a nucleic acid sample by incorporating synthetic polymorphisms into fragments of a nucleic acid sample and utilizing the synthetic polymorphisms in determining one or more haplotypes and/or phasing of haplotypes.
    Type: Grant
    Filed: February 18, 2022
    Date of Patent: March 14, 2023
    Assignee: Illumina Cambridge Limited
    Inventors: Roberto Rigatti, Jonathan Mark Boutell
  • Patent number: 11568960
    Abstract: Systems and methods for scoring and visualizing the effects of variants in biological sequences. Variants may include substitutions, insertions and deletions. The method comprises encoding biological sequences as vector sequences and then operating a neural network in the forward-propagation mode and possibly in the back-propagation mode to compute variant scores. Variant scores are determined by normalizing the gradients. Variant scores may be used to select a subset of variants, which are then used to produce modified vector sequences which are analyzed by the neural network operating in forward-propagation mode, to determine improved variant scores. The variant scores may be visualized using black and white, greyscale or colored elements that are arranged in blocks with dimensions corresponding to different possible symbols and the length of the sequence. These blocks are aligned with the biological sequence, which is illustrated by a symbol sequence arranged in a line.
    Type: Grant
    Filed: November 2, 2018
    Date of Patent: January 31, 2023
    Inventors: Andrew Delong, Brendan Frey
  • Patent number: 11551786
    Abstract: A computer-implemented method of training a neural network to improve a characteristic of a protein comprises collecting a set of amino acid sequences from a database, compiling each amino acid sequence into a three-dimensional crystallographic structure of a folded protein, training a neural network with a subset of the three-dimensional crystallographic structures, identifying, with the neural network, a candidate residue to mutate in a target protein, and identifying, with the neural network, a predicted amino acid residue to substitute for the candidate residue, to produce a mutated protein, wherein the mutated protein demonstrates an improvement in a characteristic over the target protein. A system for improving a characteristic of a protein is also described. Improved blue fluorescent proteins generated using the system are also described.
    Type: Grant
    Filed: October 27, 2021
    Date of Patent: January 10, 2023
    Assignee: Board of Regents, The University of Texas System
    Inventors: Andrew Ellington, Austin Cole, Raghav Shroff, Ross Thyer
  • Patent number: 11527305
    Abstract: Systems and methods are disclosed to detect single-nucleotide variations (SNVs) from somatic sources in a cell-free biological sample of a subject by generating training data with class labels; in computer memory, generating a machine learning unit comprising one output for each of adenine (A), cytosine (C), guanine (G), and thymine (T) calls; training the machine learning unit; and applying the machine learning unit to detect the SNVs from somatic sources in the cell-free biological sample of the subject, wherein the cell-free biological sample comprises a mixture of nucleic acid molecules from somatic and germline sources.
    Type: Grant
    Filed: February 17, 2021
    Date of Patent: December 13, 2022
    Assignee: Guardant Health, Inc.
    Inventors: Bahram Ghaffarzadeh Kermani, Helmy Eltoukhy
  • Patent number: 11521707
    Abstract: Methods, systems, apparatus, and computer programs are disclosed for software-accelerated genomic data read mapping. In one aspect, the methods can include actions of obtaining a k-mer seed from a genomic data read, generating a genomic signature based on the obtained k-mer seed, determining a reference sequence location that match at least a portion of the k-mer seed using a hash data structure, wherein the hash data structure comprises N data cells comprising a first portion storing a predetermined genomic signature and a second portion storing a value that corresponds to a first occurrence of a reference sequence location that match at least a portion of the k-mer seed from which the predetermined genomic signature was derived, and selecting the determined reference sequence location as an actual alignment for the obtained k-mer seed based on one or more alignment scores.
    Type: Grant
    Filed: September 15, 2021
    Date of Patent: December 6, 2022
    Assignee: Illumina, Inc.
    Inventor: Guillaume Alexandre Pascal Rizk