DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires

The advent of high-throughput T-cell receptor sequencing has allowed for the rapid and thorough characterization of the adaptive immune response. Here the authors show how deep learning can reveal both descriptive and predictive sequence concepts within the immune repertoire.

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Autores principales:	John-William Sidhom, H. Benjamin Larman, Drew M. Pardoll, Alexander S. Baras
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/c4e3c2b9c49b4aa788292791fd3cc408
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spelling	oai:doaj.org-article:c4e3c2b9c49b4aa788292791fd3cc4082021-12-02T15:52:37ZDeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires10.1038/s41467-021-21879-w2041-1723https://doaj.org/article/c4e3c2b9c49b4aa788292791fd3cc4082021-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21879-whttps://doaj.org/toc/2041-1723The advent of high-throughput T-cell receptor sequencing has allowed for the rapid and thorough characterization of the adaptive immune response. Here the authors show how deep learning can reveal both descriptive and predictive sequence concepts within the immune repertoire.John-William SidhomH. Benjamin LarmanDrew M. PardollAlexander S. BarasNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q John-William Sidhom H. Benjamin Larman Drew M. Pardoll Alexander S. Baras DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
description	The advent of high-throughput T-cell receptor sequencing has allowed for the rapid and thorough characterization of the adaptive immune response. Here the authors show how deep learning can reveal both descriptive and predictive sequence concepts within the immune repertoire.
format	article
author	John-William Sidhom H. Benjamin Larman Drew M. Pardoll Alexander S. Baras
author_facet	John-William Sidhom H. Benjamin Larman Drew M. Pardoll Alexander S. Baras
author_sort	John-William Sidhom
title	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
title_short	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
title_full	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
title_fullStr	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
title_full_unstemmed	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires
title_sort	deeptcr is a deep learning framework for revealing sequence concepts within t-cell repertoires
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c4e3c2b9c49b4aa788292791fd3cc408
work_keys_str_mv	AT johnwilliamsidhom deeptcrisadeeplearningframeworkforrevealingsequenceconceptswithintcellrepertoires AT hbenjaminlarman deeptcrisadeeplearningframeworkforrevealingsequenceconceptswithintcellrepertoires AT drewmpardoll deeptcrisadeeplearningframeworkforrevealingsequenceconceptswithintcellrepertoires AT alexandersbaras deeptcrisadeeplearningframeworkforrevealingsequenceconceptswithintcellrepertoires
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DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires

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