MX2021012019A - Deteccion rapida de fusiones genicas. - Google Patents

Deteccion rapida de fusiones genicas.

Info

Publication number
MX2021012019A
MX2021012019A MX2021012019A MX2021012019A MX2021012019A MX 2021012019 A MX2021012019 A MX 2021012019A MX 2021012019 A MX2021012019 A MX 2021012019A MX 2021012019 A MX2021012019 A MX 2021012019A MX 2021012019 A MX2021012019 A MX 2021012019A
Authority
MX
Mexico
Prior art keywords
fusion
data
candidates
input
candidate
Prior art date
Application number
MX2021012019A
Other languages
English (en)
Inventor
Michael Ruehle
Rami Mehio
Viraj Deshpande
Johann Felix Wilhelm Schlesinger
Sean Truong
John Cooper Roddey
Severine Catreux
Original Assignee
Illumina Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Illumina Inc filed Critical Illumina Inc
Publication of MX2021012019A publication Critical patent/MX2021012019A/es

Links

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/25Fusion techniques
    • G06F18/251Fusion techniques of input or preprocessed data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/10Sequence alignment; Homology search
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20Supervised data analysis

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Data Mining & Analysis (AREA)
  • Biotechnology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Analytical Chemistry (AREA)
  • Chemical & Material Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Computing Systems (AREA)
  • Bioethics (AREA)
  • Public Health (AREA)
  • Epidemiology (AREA)
  • Databases & Information Systems (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Genetics & Genomics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)

Abstract

Se describen métodos, sistemas y aparatos, que incluyen programas informáticos para identificar una fusión génica en una muestra biológica. El método puede incluir acciones para obtener primeros datos que representan una pluralidad de lecturas alineadas, identificar una pluralidad de candidatos a fusión incluidos dentro de los primeros datos obtenidos, filtrar la pluralidad de candidatos a fusión para determinar un conjunto filtrado de candidatos a fusión, para cada candidato particular a fusión del conjunto filtrado de candidatos a fusión: generar, mediante una o más computadoras, datos de entrada para entrada a un modelo de aprendizaje automático que incluye datos de características extraídos para representar el candidato particular a fusión, proporcionar los datos de entrada generados como una entrada al modelo de aprendizaje automático que se ha entrenado para generar datos de salida que representan una probabilidad de que un candidato a fusión sea una fusión génica válida, y determinar si el candidato particular a fusión corresponde a una fusión génica válida basada en los datos de salida.
MX2021012019A 2019-12-05 2020-12-04 Deteccion rapida de fusiones genicas. MX2021012019A (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201962944304P 2019-12-05 2019-12-05
PCT/US2020/063496 WO2021113779A1 (en) 2019-12-05 2020-12-04 Rapid detection of gene fusions

Publications (1)

Publication Number Publication Date
MX2021012019A true MX2021012019A (es) 2021-10-26

Family

ID=74004162

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2021012019A MX2021012019A (es) 2019-12-05 2020-12-04 Deteccion rapida de fusiones genicas.

Country Status (12)

Country Link
US (1) US20210193254A1 (es)
EP (1) EP4070320A1 (es)
JP (1) JP2023503739A (es)
KR (1) KR20220107117A (es)
CN (1) CN113574603A (es)
AU (1) AU2020398180A1 (es)
BR (1) BR112021018933A2 (es)
CA (1) CA3131487A1 (es)
IL (1) IL286129A (es)
MX (1) MX2021012019A (es)
SG (1) SG11202109079YA (es)
WO (1) WO2021113779A1 (es)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2024086499A1 (en) * 2022-10-17 2024-04-25 University Of Washington Systems and methods for detecting fusion genes from sequencing data
CN115662520B (zh) * 2022-10-27 2023-04-14 黑龙江金域医学检验实验室有限公司 Bcr/abl1融合基因的检测方法及相关设备

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160019340A1 (en) * 2014-07-18 2016-01-21 Life Technologies Corporation Systems and methods for detecting structural variants
BR112017007282A2 (pt) * 2014-10-10 2018-06-19 Invitae Corp métodos, sistemas e processos de montagem de novo de leituras de sequenciamento
US10354747B1 (en) * 2016-05-06 2019-07-16 Verily Life Sciences Llc Deep learning analysis pipeline for next generation sequencing
BR112019009830A2 (pt) * 2016-11-16 2019-08-13 Illumina Inc métodos para realinhamento de leitura de dados de sequenciamento
US10964410B2 (en) * 2017-05-25 2021-03-30 Koninklijke Philips N.V. System and method for detecting gene fusion
EP3639173A1 (en) * 2017-06-12 2020-04-22 Grail, Inc. Alignment free filtering for identifying fusions
CN107267646A (zh) * 2017-08-02 2017-10-20 广东国盛医学科技有限公司 一种基于下一代测序的多基因融合检测方法
US20200105373A1 (en) * 2018-09-28 2020-04-02 10X Genomics, Inc. Systems and methods for cellular analysis using nucleic acid sequencing
JP7462632B2 (ja) * 2018-11-30 2024-04-05 カリス エムピーアイ インコーポレイテッド 次世代分子プロファイリング
CN110322925B (zh) * 2019-07-18 2021-09-03 杭州纽安津生物科技有限公司 一种预测融合基因产生新生抗原的方法

Also Published As

Publication number Publication date
SG11202109079YA (en) 2021-09-29
EP4070320A1 (en) 2022-10-12
IL286129A (en) 2021-10-31
WO2021113779A1 (en) 2021-06-10
CA3131487A1 (en) 2021-06-10
AU2020398180A1 (en) 2021-09-16
US20210193254A1 (en) 2021-06-24
KR20220107117A (ko) 2022-08-02
BR112021018933A2 (pt) 2022-06-21
JP2023503739A (ja) 2023-02-01
CN113574603A (zh) 2021-10-29

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