IL271091B - Deep learning-based techniques for pre-training deep convolutional neural networks - Google Patents

Deep learning-based techniques for pre-training deep convolutional neural networks

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Publication number
IL271091B
IL271091B IL271091A IL27109119A IL271091B IL 271091 B IL271091 B IL 271091B IL 271091 A IL271091 A IL 271091A IL 27109119 A IL27109119 A IL 27109119A IL 271091 B IL271091 B IL 271091B
Authority
IL
Israel
Prior art keywords
convolutional neural
neural networks
based techniques
training
deep
Prior art date
Application number
IL271091A
Other languages
Hebrew (he)
Other versions
IL271091A (en
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
Priority claimed from US16/160,968 external-priority patent/US11798650B2/en
Priority claimed from US16/407,149 external-priority patent/US10540591B2/en
Application filed by Illumina Inc filed Critical Illumina Inc
Publication of IL271091A publication Critical patent/IL271091A/en
Publication of IL271091B publication Critical patent/IL271091B/en

Links

Classifications

    • 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
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • 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
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • 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
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/30—Detection of binding sites or motifs
    • 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
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/10—Sequence alignment; Homology search
    • 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
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
IL271091A 2018-10-15 2019-12-02 Deep learning-based techniques for pre-training deep convolutional neural networks IL271091B (en)

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
US16/160,968 US11798650B2 (en) 2017-10-16 2018-10-15 Semi-supervised learning for training an ensemble of deep convolutional neural networks
PCT/US2018/055840 WO2019079166A1 (en) 2017-10-16 2018-10-15 Deep learning-based techniques for training deep convolutional neural networks
US16/160,903 US10423861B2 (en) 2017-10-16 2018-10-15 Deep learning-based techniques for training deep convolutional neural networks
PCT/US2018/055878 WO2019079180A1 (en) 2017-10-16 2018-10-15 Deep convolutional neural networks for variant classification
PCT/US2018/055881 WO2019079182A1 (en) 2017-10-16 2018-10-15 Semi-supervised learning for training an ensemble of deep convolutional neural networks
US16/160,986 US11315016B2 (en) 2017-10-16 2018-10-15 Deep convolutional neural networks for variant classification
US16/407,149 US10540591B2 (en) 2017-10-16 2019-05-08 Deep learning-based techniques for pre-training deep convolutional neural networks
PCT/US2019/031621 WO2020081122A1 (en) 2018-10-15 2019-05-09 Deep learning-based techniques for pre-training deep convolutional neural networks

Publications (2)

Publication Number Publication Date
IL271091A IL271091A (en) 2020-04-30
IL271091B true IL271091B (en) 2021-05-31

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IL271091A IL271091B (en) 2018-10-15 2019-12-02 Deep learning-based techniques for pre-training deep convolutional neural networks
IL282689A IL282689A (en) 2018-10-15 2021-04-27 Variant pathogenicity classifier trained to avoid overfitting on position frequency matrices

Family Applications After (1)

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IL282689A IL282689A (en) 2018-10-15 2021-04-27 Variant pathogenicity classifier trained to avoid overfitting on position frequency matrices

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JP (3) JP6888123B2 (en)
KR (1) KR102165734B1 (en)
CN (2) CN113705585A (en)
AU (2) AU2019272062B2 (en)
IL (2) IL271091B (en)
NZ (1) NZ759665A (en)
SG (2) SG10202108013QA (en)
WO (1) WO2020081122A1 (en)

Families Citing this family (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111680762B (en) * 2018-11-27 2023-08-04 成都大学 Method and device for classifying suitable radix rehmanniae of traditional Chinese medicinal materials
KR102418073B1 (en) * 2020-06-08 2022-07-06 고려대학교 산학협력단 Apparatus and method for artificial intelligence based automatic analysis of video fluoroscopic swallowing study
CN111830408B (en) * 2020-06-23 2023-04-18 朗斯顿科技(北京)有限公司 Motor fault diagnosis system and method based on edge calculation and deep learning
CN112003735B (en) * 2020-07-28 2021-11-09 四川大学 Risk-aware deep learning-driven limit transmission capacity adjustment method
CN112183088B (en) * 2020-09-28 2023-11-21 云知声智能科技股份有限公司 Word level determining method, model building method, device and equipment
KR102279056B1 (en) * 2021-01-19 2021-07-19 주식회사 쓰리빌리언 System for pathogenicity prediction of genomic mutation using knowledge transfer
CN113299345B (en) * 2021-06-30 2024-05-07 中国人民解放军军事科学院军事医学研究院 Virus gene classification method and device and electronic equipment
CN113539354B (en) * 2021-07-19 2023-10-27 浙江理工大学 Method for efficiently predicting type III and type IV effector proteins of gram-negative bacteria
CN113822342B (en) * 2021-09-02 2023-05-30 湖北工业大学 Document classification method and system for security graph convolution network
CN113836892B (en) * 2021-09-08 2023-08-08 灵犀量子(北京)医疗科技有限公司 Sample size data extraction method and device, electronic equipment and storage medium
CN113963746B (en) * 2021-09-29 2023-09-19 西安交通大学 Genome structure variation detection system and method based on deep learning
US20240087683A1 (en) * 2022-09-14 2024-03-14 Microsoft Technology Licensing, Llc Classification using a machine learning model trained with triplet loss
CN115662520B (en) * 2022-10-27 2023-04-14 黑龙江金域医学检验实验室有限公司 Detection method of BCR/ABL1 fusion gene and related equipment
CN116153396A (en) * 2023-04-21 2023-05-23 鲁东大学 Non-coding variation prediction method based on transfer learning
CN117688785B (en) * 2024-02-02 2024-04-16 东北大学 Full tensor gravity gradient data inversion method based on planting thought

Family Cites Families (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2044616A1 (en) 1989-10-26 1991-04-27 Roger Y. Tsien Dna sequencing
US5641658A (en) 1994-08-03 1997-06-24 Mosaic Technologies, Inc. Method for performing amplification of nucleic acid with two primers bound to a single solid support
ATE269908T1 (en) 1997-04-01 2004-07-15 Manteia S A METHOD FOR SEQUENCING NUCLEIC ACIDS
AR021833A1 (en) 1998-09-30 2002-08-07 Applied Research Systems METHODS OF AMPLIFICATION AND SEQUENCING OF NUCLEIC ACID
GB0006153D0 (en) * 2000-03-14 2000-05-03 Inpharmatica Ltd Database
AU2001282881B2 (en) 2000-07-07 2007-06-14 Visigen Biotechnologies, Inc. Real-time sequence determination
AU2002227156A1 (en) 2000-12-01 2002-06-11 Visigen Biotechnologies, Inc. Enzymatic nucleic acid synthesis: compositions and methods for altering monomer incorporation fidelity
AR031640A1 (en) 2000-12-08 2003-09-24 Applied Research Systems ISOTHERMAL AMPLIFICATION OF NUCLEIC ACIDS IN A SOLID SUPPORT
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
US20040002090A1 (en) 2002-03-05 2004-01-01 Pascal Mayer Methods for detecting genome-wide sequence variations associated with a phenotype
ES2407681T3 (en) 2002-08-23 2013-06-13 Illumina Cambridge Limited Modified nucleotides for polynucleotide sequencing.
WO2006044078A2 (en) 2004-09-17 2006-04-27 Pacific Biosciences Of California, Inc. Apparatus and method for analysis of molecules
GB0427236D0 (en) 2004-12-13 2005-01-12 Solexa Ltd Improved method of nucleotide detection
WO2006138257A2 (en) 2005-06-15 2006-12-28 Callida Genomics, Inc. Single molecule arrays for genetic and chemical analysis
GB0514910D0 (en) 2005-07-20 2005-08-24 Solexa Ltd Method for sequencing a polynucleotide template
US7405281B2 (en) 2005-09-29 2008-07-29 Pacific Biosciences Of California, Inc. Fluorescent nucleotide analogs and uses therefor
GB0522310D0 (en) 2005-11-01 2005-12-07 Solexa Ltd Methods of preparing libraries of template polynucleotides
EP2021503A1 (en) 2006-03-17 2009-02-11 Solexa Ltd. Isothermal methods for creating clonal single molecule arrays
SG170802A1 (en) 2006-03-31 2011-05-30 Solexa Inc Systems and devices for sequence by synthesis analysis
US7754429B2 (en) 2006-10-06 2010-07-13 Illumina Cambridge Limited Method for pair-wise sequencing a plurity of target polynucleotides
US8343746B2 (en) 2006-10-23 2013-01-01 Pacific Biosciences Of California, Inc. Polymerase enzymes and reagents for enhanced nucleic acid sequencing
CA2730614A1 (en) * 2008-07-16 2010-01-21 Dana-Farber Cancer Institute Signatures and pcdeterminants associated with prostate cancer and methods of use thereof
WO2010038173A1 (en) * 2008-10-02 2010-04-08 Koninklijke Philips Electronics N.V. Method of determining a reliability indicator for signatures obtained from clinical data and use of the reliability indicator for favoring one signature over the other
JP5773406B2 (en) * 2010-07-28 2015-09-02 学校法人明治大学 GPI-anchored protein determination device, determination method, and determination program
US20130296175A1 (en) 2011-01-13 2013-11-07 Illumina Inc. Genetic Variants as Markers for Use in Urinary Bladder Cancer Risk Assessment, Diagnosis, Prognosis and Treatment
ES2875892T3 (en) * 2013-09-20 2021-11-11 Spraying Systems Co Spray nozzle for fluidized catalytic cracking
EP3194627B1 (en) 2014-09-18 2023-08-16 Illumina, Inc. Methods and systems for analyzing nucleic acid sequencing data
AU2016263026A1 (en) * 2015-05-15 2017-11-09 Pioneer Hi-Bred International, Inc. Guide RNA/Cas endonuclease systems
WO2016209999A1 (en) * 2015-06-22 2016-12-29 Counsyl, Inc. Methods of predicting pathogenicity of genetic sequence variants
CN107622182B (en) * 2017-08-04 2020-10-09 中南大学 Method and system for predicting local structural features of protein
CN108197427B (en) * 2018-01-02 2020-09-04 山东师范大学 Protein subcellular localization method and device based on deep convolutional neural network
CN108595909A (en) * 2018-03-29 2018-09-28 山东师范大学 TA targeting proteins prediction techniques based on integrated classifier

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Publication number Publication date
AU2019272062B2 (en) 2021-08-19
SG11201911777QA (en) 2020-05-28
AU2021269351B2 (en) 2023-12-14
CN113705585A (en) 2021-11-26
JP6888123B2 (en) 2021-06-16
SG10202108013QA (en) 2021-09-29
KR20200044731A (en) 2020-04-29
IL282689A (en) 2021-06-30
JP2021501923A (en) 2021-01-21
NZ759665A (en) 2022-07-01
KR102165734B1 (en) 2020-10-14
AU2021269351A1 (en) 2021-12-09
WO2020081122A1 (en) 2020-04-23
JP2021152907A (en) 2021-09-30
CN111328419B (en) 2021-10-19
AU2019272062A1 (en) 2020-04-30
JP7200294B2 (en) 2023-01-06
CN111328419A (en) 2020-06-23
JP2023052011A (en) 2023-04-11
IL271091A (en) 2020-04-30

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