专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明公开

EP1820133A2 METHOD AND SYSTEM FOR IDENTIFYING POLYPEPTIDES 有权
标题翻译： VERFAHREN UND SYSTEM ZUM IDENTIFIZIEREN VON POLYPEPTIDEN
公开(公告)号：EP1820133A2
公开(公告)日：2007-08-22
申请号：EP05816092.0
申请日：2005-10-06
申请人： Applera Corporation
发明人： SHILOV, Ignat V. , SEYMOUR, Sean L. , BONNER, Ron , PATEL, Alpesh A.
IPC分类号： G06F19/00
CPC分类号： G06F19/00 , C12N15/87 , G01N33/6842 , G01N33/6848 , G16B40/10
摘要： The present teachings provide for identification of peptides using small sequence tags to focus computational resources on searching regions of a protein database that are the most likely to yield correct identifications. They allow for the incorporation of modifications and in doing so focuses the search to peptides with a precursor mass match. Additionally, probability or relevance factors can be used to determine peptide hypotheses. Various embodiments are presented that search for peptides when a single precursor is selected or when multiple precursors are simultaneously fragmented.
摘要翻译：本教导提供使用小序列标签鉴定肽，以将计算资源集中在最有可能产生正确鉴定的蛋白质数据库的搜索区域上。它们允许引入修饰，这样做可以将搜索重点放在具有前体大量匹配的肽上。另外，可以使用概率或相关因素来确定肽假说。呈现了当选择单一前体时或当多个前体同时分裂时搜索肽的各种实施方案。

2. 发明公开

EP2569627A1 SYSTEMS AND METHODS FOR CALCULATING PROTEIN CONFIDENCE VALUES 有权
标题翻译：系统和计算方法PROTEINKONFIDENZWERTEN
公开(公告)号：EP2569627A1
公开(公告)日：2013-03-20
申请号：EP11781256.0
申请日：2011-05-12
申请人： DH Technologies Development Pte. Ltd.
发明人： SHILOV, Ignat V.
IPC分类号： G01N33/48 , G01N33/50
CPC分类号： G16C20/20 , G16B40/10
摘要： 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.

3. 发明公开

EP2430569A2 SYSTEMS AND METHODS FOR AUTOMATED MELTING CURVE ANALYSIS 有权
标题翻译：系统和方法用于自动熔解曲线分析
公开(公告)号：EP2430569A2
公开(公告)日：2012-03-21
申请号：EP10775622.3
申请日：2010-05-14
申请人： Idaho Technology, Inc. , University of Utah Research Foundation
发明人： ROBBINS, Thomas Charles , PALAIS, Robert Andrew , WITTWER, Carl Thomas
IPC分类号： G06F17/00 , G06F9/00
CPC分类号： G16B40/00 , C12Q1/6816 , G01N33/6803 , G16B20/00 , G16B25/00 , G16B25/20 , G16B40/10 , C12Q2527/107 , C12Q2537/165 , C12Q2539/101
摘要： An experimental melting curve is modeled as a sum of a true melting curve and background fluorescence. A deviation function may be generated based upon the experimental melting curve data and a model of a background signal. The deviation function may be generated by segmenting a range of the experimental curve into a plurality of windows. Within each window, a fit between the model of the background signal and the experimental melting curve data may be calculated. The deviation function may be formed from the resulting fit parameters. The deviation function may include background signal compensation and, as such, may be used in various melting curve analysis operations, such as data visualization, clustering, genotyping, scanning, negative sample removal, and the like. The deviation function may be used to seed an automated background correction process. A background-corrected melting curve may be further processed to remove an aggregation signal.

4. 发明申请

US20190194320A1 METHODS OF IDENTIFYING EPITOPES 审中-公开
公开(公告)号：US20190194320A1
公开(公告)日：2019-06-27
申请号：US16329538
申请日：2017-09-01
申请人： OBLIQUE THERAPEUTICS AB
发明人： Owe ORWAR , Carolina TRKULJA , Max DAVIDSON
IPC分类号： C07K16/28 , C07K14/705 , G16B35/20 , C07K16/00 , G16B40/10
CPC分类号： C07K16/28 , C07K14/705 , C07K16/005 , C07K2317/34 , C07K2317/77 , G01N33/68 , G16B35/20 , G16B40/10
摘要： The present invention relates to methods of identifying an epitope on a protein that can be bound by an antibody. Methods of the invention typically involve a step of limited or restricted proteolysis of a protein and the identification of sites on the protein that are cut by the protease(s) used. The invention also relates to antibodies which bind to epitopes that have been identified by methods of the invention.

5. 发明申请

US20180074038A1 METABOLOMICS PROFILING OF CENTRAL NERVOUS SYSTEM INJURY 审中-公开
公开(公告)号：US20180074038A1
公开(公告)日：2018-03-15
申请号：US15560056
申请日：2016-03-18
申请人： LONDON HEALTH SCIENCES CENTRE RESEARCH INC.
发明人： Douglas Dale FRASER , Robert BARTHA , Arthur BROWN , Tanya Charyk STEWART , Mark DALEY , Greg A. DEKABAN , Timothy DOHERTY , Lisa FISCHER , Jeff HOLMES , Ravi MENON , J. Kevin SHOEMAKER , Tony RUPAR
IPC分类号： G01N33/487 , G06F19/24
CPC分类号： G01N33/487 , G01N24/08 , G01N33/483 , G01N33/6896 , G01N2570/00 , G01N2800/28 , G01N2800/2871 , G16B40/00 , G16B40/10 , G16B40/20 , G16B40/30 , G16C20/70
摘要： A method of diagnosing central nervous system injuries such as acquired brain injury (ABI) and/or acquired spinal cord injury (ASI), including mild TBI (concussion or blast wave), mild ASI (contusion, stretch or partial cord transection), non-TBI brain injury and/or non-TSI spinal cord injury in a subject (animal or human). The method includes (a) obtaining a biological test sample from the subject, identifying metabolites in the subject's sample using metabolomics thereby obtaining a subject's metabolite matrix and generating a subject's profile using the patient's metabolite matrix; and (b) using multivariate statistical analysis and machine learning to compare the subject's profile with predetermined set of profiles of CNS injuries and a predetermined set of profiles of controls to determine if the subject has a CNS injury.

6. 发明申请

US20150051840A1 Identification Of Microorganisms By Spectrometry And Structured Classification 审中-公开
标题翻译：通过光谱法和结构分类鉴定微生物
公开(公告)号：US20150051840A1
公开(公告)日：2015-02-19
申请号：US14387777
申请日：2013-04-02
申请人： bioMerieux
发明人： Kevin Vervier , Pierre Mahe , Jean-Baptiste Veyrieras
IPC分类号： H01J49/16 , G01N33/50 , G06F19/24
CPC分类号： H01J49/164 , C12Q1/04 , G01N33/50 , G06K9/6282 , G16B40/00 , G16B40/10
摘要： A method of identifying by spectrometry of unknown microorganisms from among a set of reference species, including a first step of supervised learning of a classification model of the reference species, a second step of predicting an unknown microorganism to be identified, including acquiring a spectrum of the unknown microorganism; and applying a prediction model according to said spectrum and to the classification model to infer at least one type of microorganism to which the unknown microorganism belong. The classification model is calculated by a structured multi-class SVM algorithm applied to the nodes of a tree-like hierarchical representation of the reference species in terms of evolution and/or of clinical phenotype and having margin constraints including so-called “loss” functions quantifying a proximity between the tree nodes.
摘要翻译：一种通过在一组参考物种中鉴定未知微生物的方法，包括参考物种分类模型的监督学习的第一步骤，预测待鉴定的未知微生物的第二步骤，包括获得未知微生物; 以及根据所述光谱应用预测模型和分类模型来推断未知微生物所属的至少一种类型的微生物。分类模型通过结构化的多类SVM算法计算，该方法应用于进化和/或临床表型方面的参考物种的树状分层表示的节点，并具有包括所谓的“损失”函数的边界约束量化树节点之间的邻近度。

7. 发明申请

WO2019010410A1 SYSTEMS AND METHODS FOR GENETIC IDENTIFICATION AND ANALYSIS 审中-公开
公开(公告)号：WO2019010410A1
公开(公告)日：2019-01-10
申请号：PCT/US2018/041081
申请日：2018-07-06
申请人： MASSACHUSETTS INSTITUTE OF TECHNOLOGY , HARPER, James , HELFER, Brian, S. , ISAACSON, Joseph , MICHALEAS, Adam, M. , PETROVICK, Martha, S. , SCHWOEBEL, Eric , SHCHERBINA, Anna , FREMONT-SMITH, Philip , WATKINS, James , WACK, Edward, C.
发明人： HARPER, James , HELFER, Brian, S. , ISAACSON, Joseph , MICHALEAS, Adam, M. , PETROVICK, Martha, S. , SCHWOEBEL, Eric , SHCHERBINA, Anna , FREMONT-SMITH, Philip , WATKINS, James , WACK, Edward, C. , RICKE, Darrell, Orlyn
IPC分类号： G01N33/48 , G01N33/50
CPC分类号： C12Q1/6886 , C12Q1/68 , C12Q1/6858 , C12Q1/6869 , C12Q2600/156 , G16B40/10 , C12Q2535/122
摘要： The disclosure provides various systems and methods for identifying individuals from one or more samples. In particular, improved systems and methods of analysis are provided for handling multiple contributors, as well as systems and methods that model not only individual error rates per locus but factor in amplification of errors induced through PCR cycles. In some embodiments, modeling of error rates can be applied in multi-contributor settings to more accurately establish real alleles from artifacts. Other aspects involve application of sequencing in error modeling. Further, methods are provided for determining the presence of common individual DNA profiles in one or more complex DNA mixtures and for deconvolution of multiple complex DNA mixtures into shared individual components.

8. 发明申请

US20190237163A1 METHODS FOR FLOW SPACE QUALITY SCORE PREDICTION BY NEURAL NETWORKS 审中-公开
公开(公告)号：US20190237163A1
公开(公告)日：2019-08-01
申请号：US16245343
申请日：2019-01-11
申请人： LIFE TECHNOLOGIES CORPORATION
发明人： Chao Wang , Eugene INGERMAN
IPC分类号： G16B40/10 , G16B30/00 , G06N3/08
CPC分类号： G16B40/10 , C12Q1/6869 , G06N3/0454 , G06N3/08 , G16B30/00
摘要： An artificial neural network is applied to a plurality of flow predictor features to generate a flow space probability of error for a base call. A base quality value for the base call is determined based on the flow space probability of error. The base call and flow predictor features are based on the flow space signal measurements generated in response to the nucleotide flow to the reaction confinement region. For an array of reaction confinement regions, a plurality of parallel neural networks is applied to produce a probability of error for each reaction confinement region. A given neural network of the parallel neural networks is applied to the plurality of flow predictor features corresponding to a given reaction confinement region in the array to provide the flow space probability of error for the given reaction confinement region.

9. 发明申请

US20190233898A1 Methods and Systems for Determining Proportions of Distinct Cell Subsets 审中-公开
公开(公告)号：US20190233898A1
公开(公告)日：2019-08-01
申请号：US16226294
申请日：2018-12-19
申请人： The Board of Trustees of the Leland Stanford Junior University
发明人： Aaron M. Newman , Arash Ash Alizadeh
IPC分类号： C12Q1/6886 , G16B25/00 , G16B40/10 , G16C20/20 , C12Q1/6881 , G01N33/50 , C12Q1/6809
CPC分类号： C12Q1/6886 , C12Q1/6809 , C12Q1/6881 , C12Q2600/106 , C12Q2600/158 , G01N33/5005 , G16B25/00 , G16B40/10 , G16C20/20 , C12Q2537/165
摘要： 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.

10. 发明授权

US10007766B2 Predictive test for melanoma patient benefit from antibody drug blocking ligand activation of the T-cell programmed cell death 1 (PD-1) checkpoint protein and classifier development methods 有权
公开(公告)号：US10007766B2
公开(公告)日：2018-06-26
申请号：US15207825
申请日：2016-07-12
申请人： Biodesix, Inc.
发明人： Joanna Röder , Krista Meyer , Julia Grigorieva , Maxim Tsypin , Carlos Oliveira , Arni Steingrimsson , Heinrich Röder , Senait Asmellash , Kevin Sayers , Caroline Maher , Jeffrey Weber
IPC分类号： C12N5/00 , C12N5/02 , G06F19/00 , G01N33/574 , G01N33/68 , G06F19/24
CPC分类号： G16H50/20 , G01N33/5743 , G01N33/6851 , G01N2333/70532 , G01N2800/52 , G06F19/00 , G06F19/3456 , G06F19/3481 , G16B40/00 , G16B40/10 , G16B40/20 , G16H10/40 , G16H20/10 , G16H20/30
摘要： A method is disclosed of predicting cancer patient response to immune checkpoint inhibitors, e.g., an antibody drug blocking ligand activation of programmed cell death 1 (PD-1) or CTLA4. The method includes obtaining mass spectrometry data from a blood-based sample of the patient, obtaining integrated intensity values in the mass spectrometry data of a multitude of pre-determined mass-spectral features; and operating on the mass spectral data with a programmed computer implementing a classifier. The classifier compares the integrated intensity values with feature values of a training set of class-labeled mass spectral data obtained from a multitude of melanoma patients with a classification algorithm and generates a class label for the sample. A class label “early” or the equivalent predicts the patient is likely to obtain relatively less benefit from the antibody drug and the class label “late” or the equivalent indicates the patient is likely to obtain relatively greater benefit from the antibody drug.

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式