公开(公告)号：US20230227897A1

公开(公告)日：2023-07-20

申请号：US18001544

申请日：2021-12-16

Applicant: seeDNA Inc.

Inventor： Kibom KIM

IPC: C12Q1/6851 ,  C12Q1/686 ,  C12Q1/6886 ,  G16B20/20 ,  G16B40/10

CPC classification number: C12Q1/6851 ,  C12Q1/686 ,  C12Q1/6886 ,  G16B20/20 ,  G16B40/10 ,  C12Q2600/156

Abstract: The present invention will provide a novel technique to evaluate the reliability of the signal indicating the presence of secondary contributor nucleic acids in the analytical data of nucleic acid mix samples containing a small ratio of secondary contributor nucleic acids, such as cffDNA, ctDNA, and ddcfDNA.
Regression analysis is performed on the composite variables and fidelity obtained from linear combination of a numerical group that includes at least the secondary contributor component signal intensity and the secondary contributor component mix rate in the analysis data, and a model function for calculating the fidelity is obtained.

公开(公告)号：US11667947B2

公开(公告)日：2023-06-06

申请号：US16704052

申请日：2019-12-05

Applicant: Colgate-Palmolive Company

Inventor： Ekta Makwana ,  Carlo Daep

IPC: C12Q1/18 ,  G16B40/10 ,  C12Q1/02 ,  C12Q1/24 ,  G06F17/15

CPC classification number: C12Q1/18 ,  C12Q1/025 ,  C12Q1/24 ,  G06F17/15 ,  G16B40/10

Abstract: Described herein are methods and systems for identifying a composition having anti-pathogenic activity; evaluating the anti-pathogenic activity of a composition; measuring the metabolic function of a pathogen; and/or comparing the anti-pathogenic performance of a plurality of compositions.

公开(公告)号：US20230170049A1

公开(公告)日：2023-06-01

申请号：US17930340

申请日：2022-09-07

Applicant: MATTERWORKS INC

Inventor： Timothy KASSIS ,  Jefferson PRUYNE ,  Mark D. SIMON ,  Mimoun CADOSCH DELMAR AKERMAN ,  Jennifer CAMPBELL ,  Ana HENRIQUES DA COSTA ,  Laura KOLINSKY ,  John M. GEREMIA

IPC: G16B40/10

CPC classification number: G16B40/10

Abstract: Disclosed are methods, libraries, and samples for quantifying a target analyte in a laboratory sample including the target analyte. The methods typically include the step of estimating the amount of the target analyte in the laboratory sample from mass spectrometric data including signal intensities for the target analyte and one or more internal standards, where the mass spectrometric data are an output of a mass spectrometric analysis of a target sample produced from the laboratory sample and a predetermined amount of the one or more internal standards. The present disclosure also provides a method for analyte quantification. The method comprises adding one or more calibrators to a sample comprising one or more analytes; applying mass spectrometry (MS) to the sample; and using a trained machine learning model to determine an absolute concentration of the one or more analytes.

公开(公告)号：US20190213473A1

公开(公告)日：2019-07-11

申请号：US15863790

申请日：2018-01-05

Applicant: Illumina, Inc.

Inventor： Anindita DUTTA ,  Amirali Kia

IPC: G06N3/08 ,  G06N5/02

CPC classification number: G06N3/08 ,  C12Q1/6869 ,  G06N5/022 ,  G16B30/00 ,  G16B40/10 ,  C12Q2537/165

Abstract: The technology disclosed predicts quality of base calling during an extended optical base calling process. The base calling process includes pre-prediction base calling process cycles and at least two times as many post-prediction base calling process cycles as pre-prediction cycles. A plurality of time series from the pre-prediction base calling process cycles is given as input to a trained convolutional neural network. The convolutional neural network determines from the pre-prediction base calling process cycles, a likely overall base calling quality expected after post-prediction base calling process cycles. When the base calling process includes a sequence of paired reads, the overall base calling quality time series of the first read is also given as an additional input to the convolutional neural network to determine the likely overall base calling quality after post-prediction cycles of the second read.

公开(公告)号：US20190204296A1

公开(公告)日：2019-07-04

申请号：US16325357

申请日：2017-07-10

Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

Inventor： Marcus STOIBER ,  James BROWN

IPC: G01N33/487 ,  C12Q1/6869 ,  G16B30/00 ,  G16B40/00 ,  G16B50/00

CPC classification number: G01N33/48721 ,  C12Q1/68 ,  C12Q1/6869 ,  C12Q2563/116 ,  C12Q2565/631 ,  G16B30/00 ,  G16B40/00 ,  G16B40/10 ,  G16B50/00 ,  C12Q2537/165

Abstract: Disclosed herein are systems and methods for nanopore sequencing basecalling. In one embodiment, the method can include: receiving raw nanopore sequencing data comprising a plurality of continuous data acquisition (DAC) values corresponding to a biomolecule; normalizing the raw nanopore sequencing data to generate normalized nanopore sequencing data comprising a plurality of normalized DAC values; generating, using a first neural network (NN) and a normalized DAC value of the plurality of normalized DAC values, a vector of transformed probability values, segmenting the plurality of normalized DAC values into a plurality of discrete events; generating, using a second neural network and the event vector, an element determination of the biomolecule.

公开(公告)号：US20160363581A1

公开(公告)日：2016-12-15

申请号：US15177695

申请日：2016-06-09

Applicant: Michael PHILLIPS

Inventor： Michael PHILLIPS

IPC: G01N33/497 ,  A61B6/03 ,  A61B6/00 ,  H01J49/00

CPC classification number: G01N33/497 ,  A61B6/032 ,  A61B6/50 ,  G01N2033/4975 ,  G16B20/00 ,  G16B40/10 ,  G16B40/20 ,  G16H50/20 ,  H01J49/00

Abstract: The present invention provides a method for identifying biomarkers and generating an output indicative of lung cancer. The method for identifying biomarkers comprises the steps of collecting a breath sample from subjects known to have lung cancer and subjects known to be free of lung cancer; analyzing the collected breath samples to determine all mass ions in each of the collected breath samples using at least one time-resolved separation technique and at least one mass-resolved separation technique; identifying a subset of the determined mass ions in a processor as the biomarkers for detecting lung cancer, the subset of the determined mass ions are statistically significant for detecting lung cancer; and combining the subset of the determined mass ions in a multivariate algorithm in the processor to generate a value of a discriminant function indicating the likelihood that the subject has lung cancer.

Abstract translation: 本发明提供了鉴定生物标志物并产生指示肺癌的输出的方法。 用于鉴定生物标志物的方法包括从已知具有肺癌的受试者和已知无肺癌患者收集呼吸样品的步骤; 分析收集的呼吸样品以使用至少一种时间分辨分离技术和至少一种质量分辨分离技术来确定每个采集的呼吸样品中的所有质量离子; 将处理器中确定的质量离子的子集识别为用于检测肺癌的生物标志物，确定的质量离子的子集对于检测肺癌具有统计学意义; 以及将所确定的质量离子的子集合在所述处理器中的多变量算法中，以生成指示所述受试者患有肺癌的可能性的判别函数的值。

公开(公告)号：US20130211734A1

公开(公告)日：2013-08-15

申请号：US13697707

申请日：2011-05-12

Applicant: Ignat V. Shilov

Inventor： Ignat V. Shilov

IPC: G06F19/00

CPC classification number: G16C20/20 ,  G16B40/10

Abstract: Protein confidence values are calculated in proteomic analysis. A protein database is searched for proteins matching peptides found from mass spectrometry of a sample producing a set of proteins and a corresponding set of peptides. Peptide confidence values for the set of peptides are determined. Protein confidence values are calculated for the set of proteins based on the peptide confidence values. A protein is selected from the set of proteins with a largest protein confidence value, the largest protein confidence value is saved for the protein, the protein is removed from the set of proteins, and one or more peptides corresponding to the protein are removed from the set of peptides. Protein confidence values are recalculated for the set of proteins based on the peptide confidence values and an effect of removing the one or more peptides from the set of peptides.

Abstract translation: 在蛋白质组学分析中计算蛋白质置信度值。 搜索蛋白质数据库，从匹配产生一组蛋白质和相应肽组的样品的质谱的质谱图匹配的蛋白质。 确定该组肽的肽置信度值。 基于肽置信度值为蛋白质组计算蛋白质置信度值。 蛋白质选自具有最大蛋白质置信度值的一组蛋白质，为蛋白质节省了最大的蛋白质置信度值，蛋白质从该组蛋白质中除去，并且从蛋白质相应的一个或多个肽从 一套肽。 基于肽置信度值和从该组肽中除去一种或多种肽的效果，对蛋白质组重新计算蛋白质置信度值。

公开(公告)号：US20130090861A1

公开(公告)日：2013-04-11

申请号：US13704007

申请日：2010-06-29

Applicant: Ching Ming Lai

Inventor： Ching Ming Lai

IPC: G06F11/00 ,  G06F19/10

CPC classification number: G06F11/00 ,  G16B20/00 ,  G16B40/10 ,  G16B99/00

Abstract: A method for verifying an ILS signal for DNA processing includes obtaining the ILS signal, determining acquisition times between peaks of the ILS signal, obtaining acquisition times between peaks in reference ILS information for the ILS signal, and verifying the ILS signal based on the ILS acquisition times and the reference ILS acquisitions times. An ILS signal processor (116) includes a false peak remover (208) that removes any false peaks in an ILS signal and a signal verifier (212) that verifies the ILS signal includes only true peaks based on reference ILS information for the ILS signal.

Abstract translation: 用于验证用于DNA处理的ILS信号的方法包括获得ILS信号，确定ILS信号的峰值之间的获取时间，获得ILS信号的参考ILS信息中的峰值之间的获取时间，以及基于ILS采集来验证ILS信号 次和参考ILS采集次数。 ILS信号处理器（116）包括去除ILS信号中的任何假峰值的伪峰值去除器（208）和验证ILS信号的信号验证器（212）仅基于ILS信号的参考ILS信息仅包括真实峰值。

公开(公告)号：US12112834B2

公开(公告)日：2024-10-08

申请号：US18358655

申请日：2023-07-25

Applicant: Refana Inc.

Inventor： Marcelo Adorni Pereira

IPC: G16B40/10 ,  G01N33/49 ,  G06F18/214 ,  G06N20/00

CPC classification number: G16B40/10 ,  G01N33/49 ,  G06F18/214 ,  G06N20/00 ,  G01N2800/60

Abstract: A system, method for determining blood biomarkers implemented by a processor and memory circuitry (PMC) and a program storage device and computer program product which includes providing near infra-red spectrogram data i of a patient's living tissue; using one or more pre-trained prediction models comprising a selected number of prediction routes, and determining prediction data on a selected group of biomarkers; determining one or more biomarkers associated with a number of groups, and determining an average concentration data of said biomarkers in accordance with output data of a number of prediction routes associated with said number of groups; and generating output data indicative of estimated levels of a selected set of biomarkers for said patient.

公开(公告)号：US20240321400A1

公开(公告)日：2024-09-26

申请号：US18269838

申请日：2021-12-29

Applicant: SEEGENE, INC.

Inventor： Jae Young KIM

IPC: G16B40/10 ,  G01J3/44 ,  G01N21/64

CPC classification number: G16B40/10 ,  G01J3/4406 ,  G01N21/645 ,  G01N2021/6419 ,  G01N2021/6421 ,  G01N2021/6432 ,  G01N2021/6484

Abstract: Disclosed are an optical spectrometry-based method for detecting a target analyte in a sample and a device for detecting a target analyte in a sample using an optical spectrometer unit. Measurement is performed by effectively separating emission light from light measured by the spectrometer unit. A target nucleic acid is accurately detected, and the use of an optical filter for filtering a specific wavelength is not necessary.