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Genomics enters the deep learning era

The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is leading today to the transformation of bioinformatics through the emergence of deep genomics, the a...

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Detalles Bibliográficos
Autores principales: Routhier, Etienne, Mozziconacci, Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235815/
https://www.ncbi.nlm.nih.gov/pubmed/35769139
http://dx.doi.org/10.7717/peerj.13613
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author Routhier, Etienne
Mozziconacci, Julien
author_facet Routhier, Etienne
Mozziconacci, Julien
author_sort Routhier, Etienne
collection PubMed
description The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is leading today to the transformation of bioinformatics through the emergence of deep genomics, the application of deep learning to genomic sequences. We review here the new applications that the use of deep learning enables in the field, focusing on three aspects: the functional annotation of genomes, the sequence determinants of the genome functions and the possibility to write synthetic genomic sequences.
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spelling pubmed-92358152022-06-28 Genomics enters the deep learning era Routhier, Etienne Mozziconacci, Julien PeerJ Bioinformatics The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is leading today to the transformation of bioinformatics through the emergence of deep genomics, the application of deep learning to genomic sequences. We review here the new applications that the use of deep learning enables in the field, focusing on three aspects: the functional annotation of genomes, the sequence determinants of the genome functions and the possibility to write synthetic genomic sequences. PeerJ Inc. 2022-06-24 /pmc/articles/PMC9235815/ /pubmed/35769139 http://dx.doi.org/10.7717/peerj.13613 Text en © 2022 Routhier and Mozziconacci https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Routhier, Etienne
Mozziconacci, Julien
Genomics enters the deep learning era
title Genomics enters the deep learning era
title_full Genomics enters the deep learning era
title_fullStr Genomics enters the deep learning era
title_full_unstemmed Genomics enters the deep learning era
title_short Genomics enters the deep learning era
title_sort genomics enters the deep learning era
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235815/
https://www.ncbi.nlm.nih.gov/pubmed/35769139
http://dx.doi.org/10.7717/peerj.13613
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