Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers

Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional...

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Autores principales:	Hatice U. Osmanbeyoglu, Fumiko Shimizu, Angela Rynne-Vidal, Direna Alonso-Curbelo, Hsuan-An Chen, Hannah Y. Wen, Tsz-Lun Yeung, Petar Jelinic, Pedram Razavi, Scott W. Lowe, Samuel C. Mok, Gabriela Chiosis, Douglas A. Levine, Christina S. Leslie
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ae04ca5ec19545a0b464c26486748931
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spelling	oai:doaj.org-article:ae04ca5ec19545a0b464c264867489312021-12-02T14:35:51ZChromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers10.1038/s41467-019-12291-62041-1723https://doaj.org/article/ae04ca5ec19545a0b464c264867489312019-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-12291-6https://doaj.org/toc/2041-1723Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional programs in gynecologic and basal breast cancers.Hatice U. OsmanbeyogluFumiko ShimizuAngela Rynne-VidalDirena Alonso-CurbeloHsuan-An ChenHannah Y. WenTsz-Lun YeungPetar JelinicPedram RazaviScott W. LoweSamuel C. MokGabriela ChiosisDouglas A. LevineChristina S. LeslieNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-12 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Hatice U. Osmanbeyoglu Fumiko Shimizu Angela Rynne-Vidal Direna Alonso-Curbelo Hsuan-An Chen Hannah Y. Wen Tsz-Lun Yeung Petar Jelinic Pedram Razavi Scott W. Lowe Samuel C. Mok Gabriela Chiosis Douglas A. Levine Christina S. Leslie Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
description	Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional programs in gynecologic and basal breast cancers.
format	article
author	Hatice U. Osmanbeyoglu Fumiko Shimizu Angela Rynne-Vidal Direna Alonso-Curbelo Hsuan-An Chen Hannah Y. Wen Tsz-Lun Yeung Petar Jelinic Pedram Razavi Scott W. Lowe Samuel C. Mok Gabriela Chiosis Douglas A. Levine Christina S. Leslie
author_facet	Hatice U. Osmanbeyoglu Fumiko Shimizu Angela Rynne-Vidal Direna Alonso-Curbelo Hsuan-An Chen Hannah Y. Wen Tsz-Lun Yeung Petar Jelinic Pedram Razavi Scott W. Lowe Samuel C. Mok Gabriela Chiosis Douglas A. Levine Christina S. Leslie
author_sort	Hatice U. Osmanbeyoglu
title	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
title_short	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
title_full	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
title_fullStr	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
title_full_unstemmed	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
title_sort	chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/ae04ca5ec19545a0b464c26486748931
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Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers

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