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Combination of Single-Molecule Electrical Measurements and Machine Learning for the Identification of Single Biomolecules
[Image: see text] The development of a next-generation DNA sequencer has provided a method for electrically measuring single molecules. Methods for electrically measuring one molecule are roughly divided into methods for measuring tunneling and ion currents. These methods enable identification of a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977028/ https://www.ncbi.nlm.nih.gov/pubmed/31984250 http://dx.doi.org/10.1021/acsomega.9b03660 |
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author | Taniguchi, Masateru |
author_facet | Taniguchi, Masateru |
author_sort | Taniguchi, Masateru |
collection | PubMed |
description | [Image: see text] The development of a next-generation DNA sequencer has provided a method for electrically measuring single molecules. Methods for electrically measuring one molecule are roughly divided into methods for measuring tunneling and ion currents. These methods enable identification of a single molecule of DNA, a RNA nucleotide, or a single protein based on current histograms. However, overlapping of current histograms of molecules with similar properties has been a major barrier to identifying single molecules with high accuracy. This barrier was broken by introducing machine learning. Combining single-molecule electrical measurement and machine learning enables high-precision identification of single molecules. Highly accurate discrimination has been demonstrated for DNA nucleotides, RNA nucleotides, amino acids, sugars, viruses, and bacteria. This combination enables quantitative evaluation of molecular recognition ability. Furthermore, a device structure suitable for high-precision identification has been designed. Combining single-molecule electrical measurement with machine learning enables digital analytical chemistry that can count certain types of molecules. Digital analytical chemistry enables comprehensive analysis of chemical reactions. This new analytical method will lead to the discovery of unknown or missed valuable molecules. |
format | Online Article Text |
id | pubmed-6977028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-69770282020-01-24 Combination of Single-Molecule Electrical Measurements and Machine Learning for the Identification of Single Biomolecules Taniguchi, Masateru ACS Omega [Image: see text] The development of a next-generation DNA sequencer has provided a method for electrically measuring single molecules. Methods for electrically measuring one molecule are roughly divided into methods for measuring tunneling and ion currents. These methods enable identification of a single molecule of DNA, a RNA nucleotide, or a single protein based on current histograms. However, overlapping of current histograms of molecules with similar properties has been a major barrier to identifying single molecules with high accuracy. This barrier was broken by introducing machine learning. Combining single-molecule electrical measurement and machine learning enables high-precision identification of single molecules. Highly accurate discrimination has been demonstrated for DNA nucleotides, RNA nucleotides, amino acids, sugars, viruses, and bacteria. This combination enables quantitative evaluation of molecular recognition ability. Furthermore, a device structure suitable for high-precision identification has been designed. Combining single-molecule electrical measurement with machine learning enables digital analytical chemistry that can count certain types of molecules. Digital analytical chemistry enables comprehensive analysis of chemical reactions. This new analytical method will lead to the discovery of unknown or missed valuable molecules. American Chemical Society 2020-01-07 /pmc/articles/PMC6977028/ /pubmed/31984250 http://dx.doi.org/10.1021/acsomega.9b03660 Text en Copyright © 2020 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited. |
spellingShingle | Taniguchi, Masateru Combination of Single-Molecule Electrical Measurements and Machine Learning for the Identification of Single Biomolecules |
title | Combination of Single-Molecule Electrical Measurements
and Machine Learning for the Identification of Single Biomolecules |
title_full | Combination of Single-Molecule Electrical Measurements
and Machine Learning for the Identification of Single Biomolecules |
title_fullStr | Combination of Single-Molecule Electrical Measurements
and Machine Learning for the Identification of Single Biomolecules |
title_full_unstemmed | Combination of Single-Molecule Electrical Measurements
and Machine Learning for the Identification of Single Biomolecules |
title_short | Combination of Single-Molecule Electrical Measurements
and Machine Learning for the Identification of Single Biomolecules |
title_sort | combination of single-molecule electrical measurements
and machine learning for the identification of single biomolecules |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977028/ https://www.ncbi.nlm.nih.gov/pubmed/31984250 http://dx.doi.org/10.1021/acsomega.9b03660 |
work_keys_str_mv | AT taniguchimasateru combinationofsinglemoleculeelectricalmeasurementsandmachinelearningfortheidentificationofsinglebiomolecules |