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    METHOD FOR VERIFYING THE PRIMARY STRUCTURE OF PROTEIN
    3.
    发明申请
    METHOD FOR VERIFYING THE PRIMARY STRUCTURE OF PROTEIN 审中-公开

    公开(公告)号：US20180356425A1

    公开(公告)日：2018-12-13

    申请号：US15778534

    申请日：2016-11-23

    Applicant: Sun Jet Biotechnology Inc.

    Inventor： Yeou Guang TSAY ,  Ya-Fen CHEN

    IPC: G01N33/68 ,  G06F19/16 ,  G06F19/24

    CPC classification number: G01N33/6848 ,  G01N33/6851 ,  G01N2440/38 ,  G01N2560/00 ,  G01N2570/00 ,  G06F19/16 ,  G06F19/24

    Abstract: Disclosed herein is a method for verifying the primary structure of a protein through comparative analyses between ion clusters observed in mass spectra and a series of simulated ion clusters deduced from its putative chemical formula. The method comprises the steps of: preparing a protein sample for mass spectrometric analyses; collecting mass spectra of the protein sample; obtaining master ion cluster from a plurality of ion clusters in the mass spectra; producing a series of simulated ion clusters according to the chemical formula of the protein; finding the best fit for the master ion cluster among the series of simulated ion clusters; and verifying if said best-fit simulated ion cluster corresponds to the chemical formula of the protein.

    Method For Calibrating A Data Set Of A Target Analyte
    4.
    发明申请
    Method For Calibrating A Data Set Of A Target Analyte 审中-公开

    公开(公告)号：US20180336315A1

    公开(公告)日：2018-11-22

    申请号：US15777316

    申请日：2016-11-21

    Applicant: SEEGENE, INC.

    Inventor： Jong Yoon CHUN ,  Young Jo LEE ,  Han Bit LEE

    IPC: G06F19/28

    CPC classification number: G06F19/28 ,  C12Q1/686 ,  G06F19/24 ,  C12Q2537/165 ,  C12Q2545/101

    Abstract: The present invention relates to a method for calibrating a data set of a target analyte in a sample, wherein a normalization coefficient for calibrating the data set is provided by using a reference value, a reference cycle and the data set, and the calibrated data set is obtained by applying the normalization coefficient to the signal values of the data set. The present method is very effective in removing the inter- and intra-instrument signal variations of data sets. Furthermore, since the present method can be configured in software, the instant method is capable of being applied universally to various analytical instruments (e.g., a real-time PCR instrument) regardless of manufacturer. Accordingly, the method by the present invention would be very useful in diagnostic data analysis.

    SECURE COMMUNICATION OF SENSITIVE GENOMIC INFORMATION USING PROBABILISTIC DATA STRUCTURES
    5.
    发明申请
    SECURE COMMUNICATION OF SENSITIVE GENOMIC INFORMATION USING PROBABILISTIC DATA STRUCTURES 审中-公开

    公开(公告)号：US20180330052A1

    公开(公告)日：2018-11-15

    申请号：US15977646

    申请日：2018-05-11

    Applicant: NOBLIS, INC.

    Inventor： Tyler W. BARRUS

    IPC: G06F19/22 ,  G06F19/24 ,  G06F19/18 ,  G06F17/30 ,  G16H10/60 ,  G06F21/62 ,  G06N7/00

    CPC classification number: G06F19/22 ,  G06F17/30985 ,  G06F19/18 ,  G06F19/24 ,  G06F21/6254 ,  G06N7/005 ,  G16H10/60

    Abstract: Techniques for securely encoding, communicating, and comparing genomic information using probabilistic data structures are provided. In some embodiments, genomic information in a secure computing environment may be encoded and/or anonymized by building a probabilistic data structure that represents sub-strings of the genomic information as members of a set; the probabilistic data structure may then be securely transmitted outside the secure computing environment. In some embodiments, a probabilistic data structure representing sub-strings of sensitive genomic information as members of a set may be received in an unsecure computing environment and may be queried to generate output data indicating whether reference sub-strings are probable members of the set. In some embodiments, querying the probabilistic data structure, and other techniques of analyzing the probabilistic data structure, may be used to determine whether the sensitive genomic information corresponds to an organism associated with the reference genomic information.

    SYSTEMS AND METHODS FOR THE ANALYSIS OF PROXIMITY BINDING ASSAY DATA
    6.
    发明申请
    SYSTEMS AND METHODS FOR THE ANALYSIS OF PROXIMITY BINDING ASSAY DATA 审中-公开

    公开(公告)号：US20180330047A1

    公开(公告)日：2018-11-15

    申请号：US15967501

    申请日：2018-04-30

    Applicant: LIFE TECHNOLOGIES CORPORATION

    Inventor： Harrison Leong ,  Nivedita Sumi Majumdar ,  Elana E Swartzman

    IPC: G06F19/18 ,  G06F19/24

    CPC classification number: G06F19/18 ,  G06F19/24

    Abstract: A proximity binding assay (PBA) is performed on at least one test sample, at least one reference sample, a background sample, and one or more calibration samples using a thermal cycler instrument. Ct values are determined for at least one set of test sample data and at least one set of reference sample data. Background corrected Ct values are calculated using a corresponding value in a background sample data set. A linear range is determined for the background corrected Ct values as a function of sample quantity. A linear regression line is calculated for each linear range. One or more parameter values of an exponential model (EM) fold change formula are estimated from the one or more sets of calibration sample data. A target protein quantity and associated confidence interval are calculated using the linear regression lines and the EM fold change formula.

    METHOD FOR NEXT GENERATION SEQUENCING BASED GENETIC TESTING
    7.
    发明申请
    METHOD FOR NEXT GENERATION SEQUENCING BASED GENETIC TESTING 审中-公开

    公开(公告)号：US20180327865A1

    公开(公告)日：2018-11-15

    申请号：US15590120

    申请日：2017-05-09

    Applicant: City University of Hong Kong

    Inventor： Zicheng Zhao ,  Bowen Tan ,  Shuai Cheng Li

    IPC: C12Q1/68 ,  G06F19/14 ,  G06F19/24

    CPC classification number: C12Q1/6888 ,  C12Q2600/156 ,  G06F19/14 ,  G06F19/24

    Abstract: A next generation sequencing (NGS) based method includes applying, for one or more genetic loci, respective NGS data for genotype of a first subject, genotype of a second subject, and genotype of an alleged offspring of the first and second subjects to a statistical model calculating a value representing a likelihood the offspring is a true offspring of the first and second subjects. The NGS data includes genotype and sequencing read of the first tested subject; genotype and sequencing read of the second tested subject; and genotype and sequencing read of the alleged offspring. The statistical model utilizes a probability of the genotype of the first tested subject in a subject population; a probability of the genotype of the second tested subject in a subject population; and a probability of the genotype of the alleged offspring in a subject population.

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