AU2019270961A1 - Machine learning enabled biological polymer assembly - Google Patents

Machine learning enabled biological polymer assembly Download PDF

Info

Publication number
AU2019270961A1
AU2019270961A1 AU2019270961A AU2019270961A AU2019270961A1 AU 2019270961 A1 AU2019270961 A1 AU 2019270961A1 AU 2019270961 A AU2019270961 A AU 2019270961A AU 2019270961 A AU2019270961 A AU 2019270961A AU 2019270961 A1 AU2019270961 A1 AU 2019270961A1
Authority
AU
Australia
Prior art keywords
assembly
locations
location
learning model
nucleotide
Prior art date
Legal status (The legal status 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 status listed.)
Abandoned
Application number
AU2019270961A
Other languages
English (en)
Inventor
Minh Duc Cao
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Quantum Si Inc
Original Assignee
Quantum Si 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 Quantum Si Inc filed Critical Quantum Si Inc
Publication of AU2019270961A1 publication Critical patent/AU2019270961A1/en
Abandoned legal-status Critical Current

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
    • 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
    • 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
    • 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • 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
    • G16B15/00—ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • 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
    • 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
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/20—Sequence assembly
    • 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
    • G16B40/30—Unsupervised 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

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Informatics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Biotechnology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Data Mining & Analysis (AREA)
  • Chemical & Material Sciences (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Bioethics (AREA)
  • Databases & Information Systems (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Analytical Chemistry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Epidemiology (AREA)
  • Public Health (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Molecular Biology (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)
  • Addition Polymer Or Copolymer, Post-Treatments, Or Chemical Modifications (AREA)
AU2019270961A 2018-05-14 2019-05-13 Machine learning enabled biological polymer assembly Abandoned AU2019270961A1 (en)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201862671260P 2018-05-14 2018-05-14
US62/671,260 2018-05-14
US201862671884P 2018-05-15 2018-05-15
US62/671,884 2018-05-15
PCT/US2019/032065 WO2019222120A1 (en) 2018-05-14 2019-05-13 Machine learning enabled biological polymer assembly

Publications (1)

Publication Number Publication Date
AU2019270961A1 true AU2019270961A1 (en) 2020-11-19

Family

ID=66669118

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2019270961A Abandoned AU2019270961A1 (en) 2018-05-14 2019-05-13 Machine learning enabled biological polymer assembly

Country Status (10)

Country Link
US (1) US20190348152A1 (https=)
EP (1) EP3794596A1 (https=)
JP (1) JP2021523479A (https=)
KR (1) KR20210010488A (https=)
CN (1) CN112437961A (https=)
AU (1) AU2019270961A1 (https=)
BR (1) BR112020022257A2 (https=)
CA (1) CA3098876A1 (https=)
MX (1) MX2020012278A (https=)
WO (1) WO2019222120A1 (https=)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3624068A1 (en) * 2018-09-14 2020-03-18 Covestro Deutschland AG Method for improving prediction relating to the production of a polymer-ic produc
US11664090B2 (en) * 2020-06-11 2023-05-30 Life Technologies Corporation Basecaller with dilated convolutional neural network
EP4211691A1 (en) * 2020-09-11 2023-07-19 F. Hoffmann-La Roche AG Deep-learning-based techniques for generating a consensus sequence from multiple noisy sequences
CA3214755A1 (en) * 2021-04-09 2022-10-13 Natalie CASTELLANA Method for antibody identification from protein mixtures

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010127045A2 (en) * 2009-04-29 2010-11-04 Complete Genomics, Inc. Method and system for calling variations in a sample polynucleotide sequence with respect to a reference polynucleotide sequence
EP2718862B1 (en) * 2011-06-06 2018-10-31 Koninklijke Philips N.V. Method for assembly of nucleic acid sequence data
EP3084002A4 (en) * 2013-12-16 2017-08-23 Complete Genomics, Inc. Basecaller for dna sequencing using machine learning
CA2894317C (en) * 2015-06-15 2023-08-15 Deep Genomics Incorporated Systems and methods for classifying, prioritizing and interpreting genetic variants and therapies using a deep neural network

Also Published As

Publication number Publication date
MX2020012278A (es) 2021-01-29
JP2021523479A (ja) 2021-09-02
WO2019222120A1 (en) 2019-11-21
KR20210010488A (ko) 2021-01-27
BR112020022257A2 (pt) 2021-02-23
CN112437961A (zh) 2021-03-02
EP3794596A1 (en) 2021-03-24
US20190348152A1 (en) 2019-11-14
CA3098876A1 (en) 2019-11-21

Similar Documents

Publication Publication Date Title
US20200176082A1 (en) Analysis of nanopore signal using a machine-learning technique
US20190348152A1 (en) Machine learning enabled biological polymer assembly
KR102539188B1 (ko) 심층 컨볼루션 신경망을 트레이닝하기 위한 심층 학습-기반 기술
Gross et al. CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction
Allen et al. JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions
US20110270533A1 (en) Systems and methods for analyzing nucleic acid sequences
US20240242075A1 (en) Deep Learning-Based Pathogenicity Classifier for Promoter Single Nucleotide Variants (pSNVs)
CN112837747A (zh) 基于注意力孪生网络的蛋白质结合位点预测方法
US20250069699A1 (en) Methods and Systems for Discovery of Embedded Target Genes in Biosynthetic Gene Clusters
JP2021523479A5 (https=)
US20260004878A1 (en) Method for assuming organism or host, method for obtaining model for assuming organism or host, and computer device for performing the same
Beiko et al. GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Mechelke et al. A probabilistic model for secondary structure prediction from protein chemical shifts
EP4584789A1 (en) Pathogenicity prediction for protein mutations using amino acid score distributions
WO2005059707A2 (en) Estimating gene networks using inferential methods and biological constraints
US10937523B2 (en) Methods, systems and computer readable storage media for generating accurate nucleotide sequences
Grassi et al. A functional strategy to characterize expression Quantitative Trait Loci
Chao et al. Predicting dynamic expression patterns in budding yeast with a fungal DNA language model
Shaw Prediction of Isoform Functions and Interactions with ncRNAs via Deep Learning
JPWO2019222120A5 (https=)
US20260112469A1 (en) System and Method for Transformer-Based Network Medicine
Fujimoto et al. Learning the language of genes: representing global codon bias with deep language models
Ahsan Learning from watching evolution
Zheng Deep learning predicts the impact of non-coding genetic variants in human traits and diseases
Balaji Journey Into the Unknown: Graph and Machine Learning Based Approaches for Improved Characterization of Novel Pathogens

Legal Events

Date Code Title Description
MK5 Application lapsed section 142(2)(e) - patent request and compl. specification not accepted