Analysis approaches for the identification and prediction of N(6)-methyladenosine sites

The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m(6)A sites, in particular full-transcriptome m(6)A. And individual m(6)A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single n...

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Autores principales: Yang, Yuwei, Liu, Zhiyu, Lu, Junru, Sun, Yuqing, Fu, Yue, Pan, Min, Xie, Xueying, Ge, Qinyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980620/
https://www.ncbi.nlm.nih.gov/pubmed/36562485
http://dx.doi.org/10.1080/15592294.2022.2158284
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author Yang, Yuwei
Liu, Zhiyu
Lu, Junru
Sun, Yuqing
Fu, Yue
Pan, Min
Xie, Xueying
Ge, Qinyu
author_facet Yang, Yuwei
Liu, Zhiyu
Lu, Junru
Sun, Yuqing
Fu, Yue
Pan, Min
Xie, Xueying
Ge, Qinyu
author_sort Yang, Yuwei
collection PubMed
description The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m(6)A sites, in particular full-transcriptome m(6)A. And individual m(6)A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m(6)A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m(6)A methylation, including the experimental detection of m(6)A methylation sites, techniques of data analysis, the way of predicting m(6)A methylation sites, m(6)A methylation databases, and detection of m(6)A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area.
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spelling pubmed-99806202023-03-03 Analysis approaches for the identification and prediction of N(6)-methyladenosine sites Yang, Yuwei Liu, Zhiyu Lu, Junru Sun, Yuqing Fu, Yue Pan, Min Xie, Xueying Ge, Qinyu Epigenetics Review The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m(6)A sites, in particular full-transcriptome m(6)A. And individual m(6)A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m(6)A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m(6)A methylation, including the experimental detection of m(6)A methylation sites, techniques of data analysis, the way of predicting m(6)A methylation sites, m(6)A methylation databases, and detection of m(6)A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area. Taylor & Francis 2022-12-23 /pmc/articles/PMC9980620/ /pubmed/36562485 http://dx.doi.org/10.1080/15592294.2022.2158284 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Yang, Yuwei
Liu, Zhiyu
Lu, Junru
Sun, Yuqing
Fu, Yue
Pan, Min
Xie, Xueying
Ge, Qinyu
Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title_full Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title_fullStr Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title_full_unstemmed Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title_short Analysis approaches for the identification and prediction of N(6)-methyladenosine sites
title_sort analysis approaches for the identification and prediction of n(6)-methyladenosine sites
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980620/
https://www.ncbi.nlm.nih.gov/pubmed/36562485
http://dx.doi.org/10.1080/15592294.2022.2158284
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