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Deep learning shapes single-cell data analysis
Deep learning has tremendous potential in single-cell data analyses, but numerous challenges and possible new developments remain to be explored. In this commentary, we consider the progress, limitations, best practices and outlook of adapting deep learning methods for analysing single-cell data.
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864973/ https://www.ncbi.nlm.nih.gov/pubmed/35197610 http://dx.doi.org/10.1038/s41580-022-00466-x |
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author | Ma, Qin Xu, Dong |
author_facet | Ma, Qin Xu, Dong |
author_sort | Ma, Qin |
collection | PubMed |
description | Deep learning has tremendous potential in single-cell data analyses, but numerous challenges and possible new developments remain to be explored. In this commentary, we consider the progress, limitations, best practices and outlook of adapting deep learning methods for analysing single-cell data. |
format | Online Article Text |
id | pubmed-8864973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88649732022-02-24 Deep learning shapes single-cell data analysis Ma, Qin Xu, Dong Nat Rev Mol Cell Biol Comment Deep learning has tremendous potential in single-cell data analyses, but numerous challenges and possible new developments remain to be explored. In this commentary, we consider the progress, limitations, best practices and outlook of adapting deep learning methods for analysing single-cell data. Nature Publishing Group UK 2022-02-23 2022 /pmc/articles/PMC8864973/ /pubmed/35197610 http://dx.doi.org/10.1038/s41580-022-00466-x Text en © Springer Nature Limited 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Comment Ma, Qin Xu, Dong Deep learning shapes single-cell data analysis |
title | Deep learning shapes single-cell data analysis |
title_full | Deep learning shapes single-cell data analysis |
title_fullStr | Deep learning shapes single-cell data analysis |
title_full_unstemmed | Deep learning shapes single-cell data analysis |
title_short | Deep learning shapes single-cell data analysis |
title_sort | deep learning shapes single-cell data analysis |
topic | Comment |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864973/ https://www.ncbi.nlm.nih.gov/pubmed/35197610 http://dx.doi.org/10.1038/s41580-022-00466-x |
work_keys_str_mv | AT maqin deeplearningshapessinglecelldataanalysis AT xudong deeplearningshapessinglecelldataanalysis |