Cargando…

Deep learning models will shape the future of stem cell research

Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future o...

Descripción completa

Detalles Bibliográficos
Autores principales: Ouyang, John F., Chothani, Sonia, Rackham, Owen J.L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860061/
https://www.ncbi.nlm.nih.gov/pubmed/36630908
http://dx.doi.org/10.1016/j.stemcr.2022.11.007
_version_ 1784874490546618368
author Ouyang, John F.
Chothani, Sonia
Rackham, Owen J.L.
author_facet Ouyang, John F.
Chothani, Sonia
Rackham, Owen J.L.
author_sort Ouyang, John F.
collection PubMed
description Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable.
format Online
Article
Text
id pubmed-9860061
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-98600612023-01-22 Deep learning models will shape the future of stem cell research Ouyang, John F. Chothani, Sonia Rackham, Owen J.L. Stem Cell Reports Perspective Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable. Elsevier 2023-01-10 /pmc/articles/PMC9860061/ /pubmed/36630908 http://dx.doi.org/10.1016/j.stemcr.2022.11.007 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Perspective
Ouyang, John F.
Chothani, Sonia
Rackham, Owen J.L.
Deep learning models will shape the future of stem cell research
title Deep learning models will shape the future of stem cell research
title_full Deep learning models will shape the future of stem cell research
title_fullStr Deep learning models will shape the future of stem cell research
title_full_unstemmed Deep learning models will shape the future of stem cell research
title_short Deep learning models will shape the future of stem cell research
title_sort deep learning models will shape the future of stem cell research
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860061/
https://www.ncbi.nlm.nih.gov/pubmed/36630908
http://dx.doi.org/10.1016/j.stemcr.2022.11.007
work_keys_str_mv AT ouyangjohnf deeplearningmodelswillshapethefutureofstemcellresearch
AT chothanisonia deeplearningmodelswillshapethefutureofstemcellresearch
AT rackhamowenjl deeplearningmodelswillshapethefutureofstemcellresearch