Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Regulatory and coding regions of genes are shaped by evolution to control expression levels. Here, the authors use deep learning to identify rules controlling gene expression levels and suggest that all parts of the gene regulatory structure interact in this.

Bibliographic Details
Main Authors:	Jan Zrimec, Christoph S. Börlin, Filip Buric, Azam Sheikh Muhammad, Rhongzen Chen, Verena Siewers, Vilhelm Verendel, Jens Nielsen, Mats Töpel, Aleksej Zelezniak
Format:	Article
Language:	English
Published:	Nature Publishing Group 2020-12-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-020-19921-4

id	doaj-a9186003c7214e17a2d079a1c50e08ae
record_format	Article
spelling	doaj-a9186003c7214e17a2d079a1c50e08ae2021-05-11T08:03:35ZengNature Publishing GroupNature Communications2041-17232020-12-0111111610.1038/s41467-020-19921-4Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structureJan Zrimec0Christoph S. Börlin1Filip Buric2Azam Sheikh Muhammad3Rhongzen Chen4Verena Siewers5Vilhelm Verendel6Jens Nielsen7Mats Töpel8Aleksej Zelezniak9Department of Biology and Biological Engineering, Chalmers University of TechnologyDepartment of Biology and Biological Engineering, Chalmers University of TechnologyDepartment of Biology and Biological Engineering, Chalmers University of TechnologyComputer Science and Engineering, Chalmers University of TechnologyComputer Science and Engineering, Chalmers University of TechnologyDepartment of Biology and Biological Engineering, Chalmers University of TechnologyComputer Science and Engineering, Chalmers University of TechnologyDepartment of Biology and Biological Engineering, Chalmers University of TechnologyDepartment of Marine Sciences, University of GothenburgDepartment of Biology and Biological Engineering, Chalmers University of TechnologyRegulatory and coding regions of genes are shaped by evolution to control expression levels. Here, the authors use deep learning to identify rules controlling gene expression levels and suggest that all parts of the gene regulatory structure interact in this.https://doi.org/10.1038/s41467-020-19921-4
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Jan Zrimec Christoph S. Börlin Filip Buric Azam Sheikh Muhammad Rhongzen Chen Verena Siewers Vilhelm Verendel Jens Nielsen Mats Töpel Aleksej Zelezniak
spellingShingle	Jan Zrimec Christoph S. Börlin Filip Buric Azam Sheikh Muhammad Rhongzen Chen Verena Siewers Vilhelm Verendel Jens Nielsen Mats Töpel Aleksej Zelezniak Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure Nature Communications
author_facet	Jan Zrimec Christoph S. Börlin Filip Buric Azam Sheikh Muhammad Rhongzen Chen Verena Siewers Vilhelm Verendel Jens Nielsen Mats Töpel Aleksej Zelezniak
author_sort	Jan Zrimec
title	Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
title_short	Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
title_full	Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
title_fullStr	Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
title_full_unstemmed	Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
title_sort	deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2020-12-01
description	Regulatory and coding regions of genes are shaped by evolution to control expression levels. Here, the authors use deep learning to identify rules controlling gene expression levels and suggest that all parts of the gene regulatory structure interact in this.
url	https://doi.org/10.1038/s41467-020-19921-4
work_keys_str_mv	AT janzrimec deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT christophsborlin deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT filipburic deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT azamsheikhmuhammad deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT rhongzenchen deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT verenasiewers deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT vilhelmverendel deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT jensnielsen deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT matstopel deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure AT aleksejzelezniak deeplearningsuggeststhatgeneexpressionisencodedinallpartsofacoevolvinginteractinggeneregulatorystructure
_version_	1721451188880146432

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Similar Items