AU2020253345B2 - Automated detection of boundaries in mass spectrometry data - Google Patents

Automated detection of boundaries in mass spectrometry data Download PDF

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AU2020253345B2
AU2020253345B2 AU2020253345A AU2020253345A AU2020253345B2 AU 2020253345 B2 AU2020253345 B2 AU 2020253345B2 AU 2020253345 A AU2020253345 A AU 2020253345A AU 2020253345 A AU2020253345 A AU 2020253345A AU 2020253345 B2 AU2020253345 B2 AU 2020253345B2
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peak
data
points
predictions
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AU2020253345A1 (en
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Daniel SERIE
Zhenqin WU
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Venn Biosciences Corp
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    • G—PHYSICS
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    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

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  • Evolutionary Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
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AU2020253345A 2019-03-29 2020-03-27 Automated detection of boundaries in mass spectrometry data Active AU2020253345B2 (en)

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US201962826228P 2019-03-29 2019-03-29
US62/826,228 2019-03-29
PCT/US2020/025502 WO2020205649A1 (en) 2019-03-29 2020-03-27 Automated detection of boundaries in mass spectrometry data

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AU2020253345A1 AU2020253345A1 (en) 2021-11-11
AU2020253345B2 true AU2020253345B2 (en) 2025-04-24

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EP (1) EP3948874A1 (enExample)
JP (2) JP7596290B2 (enExample)
KR (1) KR20210145210A (enExample)
CN (1) CN113785362A (enExample)
AU (1) AU2020253345B2 (enExample)
BR (1) BR112021019514A2 (enExample)
CA (1) CA3131254A1 (enExample)
IL (1) IL286676A (enExample)
PH (1) PH12021552421A1 (enExample)
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Families Citing this family (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20210145210A (ko) 2019-03-29 2021-12-01 벤 바이오사이언시스 코포레이션 질량 분석 데이터의 경계 자동 검출
US11644470B2 (en) * 2019-04-15 2023-05-09 Bioinformatics Solutions Inc. Systems and methods for de novo peptide sequencing using deep learning and spectrum pairs
CN114391099B (zh) * 2019-10-02 2025-12-02 株式会社岛津制作所 波形解析方法和波形解析装置
CN115244397B (zh) * 2020-03-16 2025-12-02 豪夫迈·罗氏有限公司 用于lc-ms的质量控制工具
CN112614550B (zh) * 2020-12-17 2024-03-15 华东理工大学 一种基于神经网络的分子筛x射线衍射图谱峰位置的预测方法
CN113780430B (zh) * 2021-09-14 2024-05-24 天津国科医疗科技发展有限公司 一种基于Hopfield模型的三重四极杆质谱仪谱图分类方法
CN113866817A (zh) * 2021-09-28 2021-12-31 中南大学 基于神经网络的中子衍射峰位预测方法、设备和介质
EP4409035A4 (en) 2021-09-30 2026-01-07 Venn Biosciences Corp SYSTEMS AND METHODS FOR DETERMINING GLYCOPEPTIDE CONCENTRATION, DETERMINING STANDARDIZED ABUNDANCE, AND PREPARING SAMPLES FOR LC/MS
WO2023075591A1 (en) 2021-10-29 2023-05-04 Venn Biosciences Corporation Ai-driven glycoproteomics liquid biopsy in nasopharyngeal carcinoma
CN113933373B (zh) * 2021-12-16 2022-02-22 成都健数科技有限公司 一种利用质谱数据确定有机物结构的方法和系统
US12158415B2 (en) * 2022-04-12 2024-12-03 2S Water Incorporated Detection of water contamination based on spectrographic analysis
CN114755357B (zh) * 2022-04-14 2025-02-11 武汉迈特维尔生物科技有限公司 一种色谱质谱自动积分方法、系统、设备、介质
US12437981B2 (en) * 2022-05-20 2025-10-07 Sapient Bioanalytics, Llc Adjustments of mass spectrometry signals
CN115171790B (zh) * 2022-07-05 2026-06-12 西湖欧米(杭州)生物科技有限公司 质谱的数据序列在质量评估中的分析方法、装置和存储介质
CN115171805A (zh) * 2022-07-23 2022-10-11 苏州青山生物科技有限公司 用于分辨生物分子质谱成像的系统及其使用方法
US20240046469A1 (en) * 2022-08-05 2024-02-08 Shanghai United Imaging Healthcare Co., Ltd. Systems and methods for signal processing
EP4390390A1 (en) * 2022-12-19 2024-06-26 Ares Trading S.A. Method for determining peak characteristics on analytical data sets
WO2024133265A1 (en) * 2022-12-19 2024-06-27 Ares Trading S.A. Method for determining peak characteristics on analytical data sets
JP2026505709A (ja) * 2023-01-11 2026-02-18 プレドミックス ヘルス サイエンシーズ プライベート リミテッド 複数の癌の早期検出のための新規のシステム及び方法
JP2024152037A (ja) * 2023-04-13 2024-10-25 株式会社島津製作所 波形解析方法、波形解析装置、及び分析装置
WO2024261533A2 (en) * 2023-06-03 2024-12-26 Clarity Bio Systems India Pvt. Ltd. Identifying and quantifying probable principal ions in ion-mobility domain of mass spectrometry data
WO2025022464A1 (en) * 2023-07-27 2025-01-30 Clarity Bio Systems India Private Limited Identifying and quantifying list of probable principal ions in chromatographic dimension present in a material
US12056443B1 (en) * 2023-12-13 2024-08-06 nference, inc. Apparatus and method for generating annotations for electronic records
CN119355483B (zh) * 2024-10-09 2026-03-24 电子科技大学 一种基于数据驱动的射频电路板故障诊断方法
CN119673311B (zh) * 2024-12-17 2025-09-26 华中科技大学 一种挥发性有机化合物色谱峰保留时间的预测方法及系统

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3130139B2 (ja) * 1992-09-17 2001-01-31 株式会社日立製作所 クロマトグラム解析方法及びクロマトグラフ装置
US20060255258A1 (en) 2005-04-11 2006-11-16 Yongdong Wang Chromatographic and mass spectral date analysis
GB2466732B (en) 2007-10-30 2011-12-21 Schlumberger Holdings Chromatography data processing method and system
US20180179499A1 (en) * 2015-06-04 2018-06-28 Bioamber Inc. Biobased production of functionalized alpha-substituted acrylates and c4-dicarboxylates
US10410113B2 (en) 2016-01-14 2019-09-10 Preferred Networks, Inc. Time series data adaptation and sensor fusion systems, methods, and apparatus
CN109416926A (zh) * 2016-04-11 2019-03-01 迪森德克斯公司 质谱数据分析工作流程
CN106586814A (zh) * 2016-12-23 2017-04-26 青岛蓝天创先科技服务有限公司 一种自动卸货的散件货物吊运箱
JP6988158B2 (ja) 2017-05-11 2022-01-05 株式会社島津製作所 液体クロマトグラフ質量分析方法及び液体クロマトグラフ質量分析装置
AU2018324195B2 (en) 2017-09-01 2024-12-12 Venn Biosciences Corporation Identification and use of glycopeptides as biomarkers for diagnosis and treatment monitoring
JP2021500539A (ja) 2017-10-18 2021-01-07 ヴェン バイオサイエンシズ コーポレーション 診断及び治療モニタリングのための生体パラメータの同定及び使用
WO2019092836A1 (ja) 2017-11-09 2019-05-16 富士通株式会社 波形解析装置
MX2021004649A (es) * 2018-10-31 2021-12-10 Regeneron Pharma Método y sistema para la identificacion y cuantificacion de una proteína.
AU2020216996B2 (en) 2019-02-01 2026-05-21 Venn Biosciences Corporation Biomarkers for diagnosing ovarian cancer
KR20210145210A (ko) * 2019-03-29 2021-12-01 벤 바이오사이언시스 코포레이션 질량 분석 데이터의 경계 자동 검출

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GALLANT S R ET AL: "Deconvolution of overlapping chromatographic peaks using a cerebellar model arithmetic computer neural network", CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, vol. 18, no. 1, 1 January 1993 (1993-01-01), pages 41 - 57 *
SHADI TOGHI ESHGHI ET AL: "Quality assessment and interference detection in targeted mass spectrometry data using machine learning", CLINICAL PROTEOMICS, SPRINGER, US, vol. 15, no. 1, 6 October 2018 (2018-10-06), pages 1 - 13 *

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US11869634B2 (en) 2024-01-09
WO2020205649A1 (en) 2020-10-08
BR112021019514A2 (pt) 2021-12-07
JP7596290B2 (ja) 2024-12-09
US20240371473A1 (en) 2024-11-07
CA3131254A1 (en) 2020-10-08
US12094575B2 (en) 2024-09-17
WO2020205649A9 (en) 2021-05-14
JP2025041616A (ja) 2025-03-26
SG11202110748QA (en) 2021-10-28
CN113785362A (zh) 2021-12-10
US20200372973A1 (en) 2020-11-26
US20240257916A1 (en) 2024-08-01
KR20210145210A (ko) 2021-12-01
JP2022525427A (ja) 2022-05-13
IL286676A (en) 2021-12-01
US12456544B2 (en) 2025-10-28
PH12021552421A1 (en) 2022-07-11
EP3948874A1 (en) 2022-02-09
AU2020253345A1 (en) 2021-11-11

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