Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping

Current methods to generate sequence-function data at large scale are either technically complex or limited to specific applications. Here the authors introduce DNA-based phenotypic recording to overcome these limitations and enable deep learning for accurate prediction of function from sequence.

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Autores principales:	Simon Höllerer, Laetitia Papaxanthos, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt, Yaakov Benenson, Markus Jeschek
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/5cdab11544394bd78e7fc3880bbaa8e2
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spelling	oai:doaj.org-article:5cdab11544394bd78e7fc3880bbaa8e22021-12-02T18:36:59ZLarge-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping10.1038/s41467-020-17222-42041-1723https://doaj.org/article/5cdab11544394bd78e7fc3880bbaa8e22020-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-17222-4https://doaj.org/toc/2041-1723Current methods to generate sequence-function data at large scale are either technically complex or limited to specific applications. Here the authors introduce DNA-based phenotypic recording to overcome these limitations and enable deep learning for accurate prediction of function from sequence.Simon HöllererLaetitia PapaxanthosAnja Cathrin GumpingerKatrin FischerChristian BeiselKarsten BorgwardtYaakov BenensonMarkus JeschekNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Simon Höllerer Laetitia Papaxanthos Anja Cathrin Gumpinger Katrin Fischer Christian Beisel Karsten Borgwardt Yaakov Benenson Markus Jeschek Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
description	Current methods to generate sequence-function data at large scale are either technically complex or limited to specific applications. Here the authors introduce DNA-based phenotypic recording to overcome these limitations and enable deep learning for accurate prediction of function from sequence.
format	article
author	Simon Höllerer Laetitia Papaxanthos Anja Cathrin Gumpinger Katrin Fischer Christian Beisel Karsten Borgwardt Yaakov Benenson Markus Jeschek
author_facet	Simon Höllerer Laetitia Papaxanthos Anja Cathrin Gumpinger Katrin Fischer Christian Beisel Karsten Borgwardt Yaakov Benenson Markus Jeschek
author_sort	Simon Höllerer
title	Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
title_short	Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
title_full	Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
title_fullStr	Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
title_full_unstemmed	Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
title_sort	large-scale dna-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/5cdab11544394bd78e7fc3880bbaa8e2
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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping

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