Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact

Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. Here, authors present a deep learning-based approach to characterise how chromatin structure relates to transcriptional state of individual cells and...

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Autores principales:	Aparna R. Rajpurkar, Leslie J. Mateo, Sedona E. Murphy, Alistair N. Boettiger
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6709defa5d6e4be39868c3cea25d7942
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spelling	oai:doaj.org-article:6709defa5d6e4be39868c3cea25d79422021-12-02T17:52:19ZDeep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact10.1038/s41467-021-23831-42041-1723https://doaj.org/article/6709defa5d6e4be39868c3cea25d79422021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23831-4https://doaj.org/toc/2041-1723Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. Here, authors present a deep learning-based approach to characterise how chromatin structure relates to transcriptional state of individual cells and determine which structural features of chromatin regulation are important for gene expression state.Aparna R. RajpurkarLeslie J. MateoSedona E. MurphyAlistair N. BoettigerNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Aparna R. Rajpurkar Leslie J. Mateo Sedona E. Murphy Alistair N. Boettiger Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
description	Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. Here, authors present a deep learning-based approach to characterise how chromatin structure relates to transcriptional state of individual cells and determine which structural features of chromatin regulation are important for gene expression state.
format	article
author	Aparna R. Rajpurkar Leslie J. Mateo Sedona E. Murphy Alistair N. Boettiger
author_facet	Aparna R. Rajpurkar Leslie J. Mateo Sedona E. Murphy Alistair N. Boettiger
author_sort	Aparna R. Rajpurkar
title	Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
title_short	Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
title_full	Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
title_fullStr	Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
title_full_unstemmed	Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact
title_sort	deep learning connects dna traces to transcription to reveal predictive features beyond enhancer–promoter contact
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6709defa5d6e4be39868c3cea25d7942
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Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact

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