CA3132181A1 - Identification of convergent antibody specificity sequence patterns - Google Patents

Identification of convergent antibody specificity sequence patterns Download PDF

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Publication number
CA3132181A1
CA3132181A1 CA3132181A CA3132181A CA3132181A1 CA 3132181 A1 CA3132181 A1 CA 3132181A1 CA 3132181 A CA3132181 A CA 3132181A CA 3132181 A CA3132181 A CA 3132181A CA 3132181 A1 CA3132181 A1 CA 3132181A1
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protein
amino acid
peptide
antigen
cell
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French (fr)
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Simon FRIEDENSOHN
Sai Reddy
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Eidgenoessische Technische Hochschule Zurich ETHZ
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Eidgenoessische Technische Hochschule Zurich ETHZ
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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
    • 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
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
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    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • 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
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    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
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    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G06N3/0455—Auto-encoder networks; Encoder-decoder networks
    • 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
    • G06N3/047—Probabilistic or stochastic networks
    • 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
    • G06N3/0475—Generative networks
    • 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
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • 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
    • G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised learning
    • 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
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic 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
    • G16B20/30—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
    • 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

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Medical Informatics (AREA)
  • Biotechnology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Evolutionary Biology (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Genetics & Genomics (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Probability & Statistics with Applications (AREA)
  • Computational Mathematics (AREA)
  • Algebra (AREA)
  • Mathematical Analysis (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Bioethics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Databases & Information Systems (AREA)
  • Epidemiology (AREA)
  • Public Health (AREA)
  • Peptides Or Proteins (AREA)
CA3132181A 2019-05-03 2020-05-02 Identification of convergent antibody specificity sequence patterns Pending CA3132181A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201962843010P 2019-05-03 2019-05-03
US62/843,010 2019-05-03
PCT/IB2020/054171 WO2020225693A1 (en) 2019-05-03 2020-05-02 Identification of convergent antibody specificity sequence patterns

Publications (1)

Publication Number Publication Date
CA3132181A1 true CA3132181A1 (en) 2020-11-12

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Family Applications (1)

Application Number Title Priority Date Filing Date
CA3132181A Pending CA3132181A1 (en) 2019-05-03 2020-05-02 Identification of convergent antibody specificity sequence patterns

Country Status (8)

Country Link
US (1) US20220164627A1 (https=)
EP (1) EP3963590A1 (https=)
JP (2) JP7602484B2 (https=)
CN (2) CN114026645A (https=)
AU (1) AU2020269607B2 (https=)
CA (1) CA3132181A1 (https=)
IL (1) IL287237A (https=)
WO (1) WO2020225693A1 (https=)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3956896A4 (en) * 2019-05-19 2022-06-22 Just-Evotec Biologics, Inc. Generation of protein sequences using machine learning techniques
CN116895350A (zh) * 2023-08-04 2023-10-17 辽宁工业大学 一种在复合位移加载下波纹管的多轴疲劳寿命预测方法

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA3160429A1 (en) * 2019-12-06 2021-06-10 Philip M. KIM System and method for generating a protein sequence
US11388356B1 (en) * 2021-04-12 2022-07-12 Tetramem Inc. AI fusion pixel sensor using memristors
CN113393900B (zh) * 2021-06-09 2022-08-02 吉林大学 基于改进Transformer模型的RNA状态推断研究方法
US20250191674A1 (en) * 2022-02-28 2025-06-12 Genentech, Inc. Protein design with segment preservation
US12587274B2 (en) 2023-03-28 2026-03-24 Quantum Generative Materials Llc Satellite optimization management system based on natural language input and artificial intelligence
WO2025074981A1 (ja) * 2023-10-04 2025-04-10 国立大学法人大阪大学 抗体選別方法、コンピュータプログラム及び情報処理装置
US12368503B2 (en) 2023-12-27 2025-07-22 Quantum Generative Materials Llc Intent-based satellite transmit management based on preexisting historical location and machine learning
US12603701B2 (en) 2023-12-27 2026-04-14 Quantum Generative Materials Llc Distributed satellite constellation management and control system

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8716195B2 (en) 2005-11-14 2014-05-06 Bioren, Inc. Antibody ultrahumanization by predicted mature CDR blasting and cohort library generation and screening
US20230019590A1 (en) * 2010-03-23 2023-01-19 Iogenetics, Llc Bioinformatic processes for determination of peptide binding
CN108138244A (zh) 2015-09-18 2018-06-08 纽约市哥伦比亚大学理事会 病毒组捕获测序平台、设计和构建方法以及使用方法
US11573239B2 (en) * 2017-07-17 2023-02-07 Bioinformatics Solutions Inc. Methods and systems for de novo peptide sequencing using deep learning
EP3486816A1 (en) * 2017-11-16 2019-05-22 Institut Pasteur Method, device, and computer program for generating protein sequences with autoregressive neural networks
CN108549794B (zh) * 2018-03-29 2021-05-25 中国林业科学研究院资源昆虫研究所 一种蛋白质二级结构预测方法
US20220180975A1 (en) * 2019-01-28 2022-06-09 The Broad Institute, Inc. Methods and systems for determining gene expression profiles and cell identities from multi-omic imaging data

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3956896A4 (en) * 2019-05-19 2022-06-22 Just-Evotec Biologics, Inc. Generation of protein sequences using machine learning techniques
US11587645B2 (en) 2019-05-19 2023-02-21 Just-Evotec Biologics, Inc. Generation of protein sequences using machine learning techniques
CN116895350A (zh) * 2023-08-04 2023-10-17 辽宁工业大学 一种在复合位移加载下波纹管的多轴疲劳寿命预测方法
CN116895350B (zh) * 2023-08-04 2024-01-16 辽宁工业大学 一种在复合位移加载下波纹管的多轴疲劳寿命预测方法

Also Published As

Publication number Publication date
AU2020269607B2 (en) 2025-12-11
JP2024167413A (ja) 2024-12-03
IL287237A (en) 2021-12-01
US20220164627A1 (en) 2022-05-26
CN114026645A (zh) 2022-02-08
EP3963590A1 (en) 2022-03-09
JP2022530941A (ja) 2022-07-05
WO2020225693A1 (en) 2020-11-12
JP7602484B2 (ja) 2024-12-18
CN120526845A (zh) 2025-08-22
AU2020269607A1 (en) 2021-10-28

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