Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors

Transcriptional factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes in a complex and redundant regulatory network. Here, the authors construct the transcription regulatory network in maize leaf using 104 TFs ChIP-seq data and train machine learning models to predi...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Xiaoyu Tu, María Katherine Mejía-Guerra, Jose A. Valdes Franco, David Tzeng, Po-Yu Chu, Wei Shen, Yingying Wei, Xiuru Dai, Pinghua Li, Edward S. Buckler, Silin Zhong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ab27a8e4e9b64591b6b5f6f82b51efc6
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ab27a8e4e9b64591b6b5f6f82b51efc6
record_format	dspace
spelling	oai:doaj.org-article:ab27a8e4e9b64591b6b5f6f82b51efc62021-12-02T19:16:24ZReconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors10.1038/s41467-020-18832-82041-1723https://doaj.org/article/ab27a8e4e9b64591b6b5f6f82b51efc62020-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18832-8https://doaj.org/toc/2041-1723Transcriptional factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes in a complex and redundant regulatory network. Here, the authors construct the transcription regulatory network in maize leaf using 104 TFs ChIP-seq data and train machine learning models to predict TF binding and colocalization.Xiaoyu TuMaría Katherine Mejía-GuerraJose A. Valdes FrancoDavid TzengPo-Yu ChuWei ShenYingying WeiXiuru DaiPinghua LiEdward S. BucklerSilin ZhongNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Xiaoyu Tu María Katherine Mejía-Guerra Jose A. Valdes Franco David Tzeng Po-Yu Chu Wei Shen Yingying Wei Xiuru Dai Pinghua Li Edward S. Buckler Silin Zhong Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
description	Transcriptional factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes in a complex and redundant regulatory network. Here, the authors construct the transcription regulatory network in maize leaf using 104 TFs ChIP-seq data and train machine learning models to predict TF binding and colocalization.
format	article
author	Xiaoyu Tu María Katherine Mejía-Guerra Jose A. Valdes Franco David Tzeng Po-Yu Chu Wei Shen Yingying Wei Xiuru Dai Pinghua Li Edward S. Buckler Silin Zhong
author_facet	Xiaoyu Tu María Katherine Mejía-Guerra Jose A. Valdes Franco David Tzeng Po-Yu Chu Wei Shen Yingying Wei Xiuru Dai Pinghua Li Edward S. Buckler Silin Zhong
author_sort	Xiaoyu Tu
title	Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
title_short	Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
title_full	Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
title_fullStr	Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
title_full_unstemmed	Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
title_sort	reconstructing the maize leaf regulatory network using chip-seq data of 104 transcription factors
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/ab27a8e4e9b64591b6b5f6f82b51efc6
work_keys_str_mv	AT xiaoyutu reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT mariakatherinemejiaguerra reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT joseavaldesfranco reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT davidtzeng reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT poyuchu reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT weishen reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT yingyingwei reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT xiurudai reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT pinghuali reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT edwardsbuckler reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors AT silinzhong reconstructingthemaizeleafregulatorynetworkusingchipseqdataof104transcriptionfactors
_version_	1718376930231713792

Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors

Ejemplares similares