Charting differentially methylated regions in cancer with Rocker-meth

Matteo Benelli et al. present Rocker-meth, a new Hidden Markov Model (HMM)-based method, to robustly identify differentially methylated regions (DMRs). They use Rocker-meth to analyse more than 6000 methylation profiles across 14 cancer types, providing a catalog of tumor-specific and shared DMRs.

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Autores principales:	Matteo Benelli, Gian Marco Franceschini, Alberto Magi, Dario Romagnoli, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Francesca Demichelis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/2d3834fd736a4fd896630a6f3d833ab9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:2d3834fd736a4fd896630a6f3d833ab92021-11-07T12:19:45ZCharting differentially methylated regions in cancer with Rocker-meth10.1038/s42003-021-02761-32399-3642https://doaj.org/article/2d3834fd736a4fd896630a6f3d833ab92021-11-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02761-3https://doaj.org/toc/2399-3642Matteo Benelli et al. present Rocker-meth, a new Hidden Markov Model (HMM)-based method, to robustly identify differentially methylated regions (DMRs). They use Rocker-meth to analyse more than 6000 methylation profiles across 14 cancer types, providing a catalog of tumor-specific and shared DMRs.Matteo BenelliGian Marco FranceschiniAlberto MagiDario RomagnoliChiara BiagioniIlenia MigliaccioLuca MalorniFrancesca DemichelisNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Matteo Benelli Gian Marco Franceschini Alberto Magi Dario Romagnoli Chiara Biagioni Ilenia Migliaccio Luca Malorni Francesca Demichelis Charting differentially methylated regions in cancer with Rocker-meth
description	Matteo Benelli et al. present Rocker-meth, a new Hidden Markov Model (HMM)-based method, to robustly identify differentially methylated regions (DMRs). They use Rocker-meth to analyse more than 6000 methylation profiles across 14 cancer types, providing a catalog of tumor-specific and shared DMRs.
format	article
author	Matteo Benelli Gian Marco Franceschini Alberto Magi Dario Romagnoli Chiara Biagioni Ilenia Migliaccio Luca Malorni Francesca Demichelis
author_facet	Matteo Benelli Gian Marco Franceschini Alberto Magi Dario Romagnoli Chiara Biagioni Ilenia Migliaccio Luca Malorni Francesca Demichelis
author_sort	Matteo Benelli
title	Charting differentially methylated regions in cancer with Rocker-meth
title_short	Charting differentially methylated regions in cancer with Rocker-meth
title_full	Charting differentially methylated regions in cancer with Rocker-meth
title_fullStr	Charting differentially methylated regions in cancer with Rocker-meth
title_full_unstemmed	Charting differentially methylated regions in cancer with Rocker-meth
title_sort	charting differentially methylated regions in cancer with rocker-meth
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2d3834fd736a4fd896630a6f3d833ab9
work_keys_str_mv	AT matteobenelli chartingdifferentiallymethylatedregionsincancerwithrockermeth AT gianmarcofranceschini chartingdifferentiallymethylatedregionsincancerwithrockermeth AT albertomagi chartingdifferentiallymethylatedregionsincancerwithrockermeth AT darioromagnoli chartingdifferentiallymethylatedregionsincancerwithrockermeth AT chiarabiagioni chartingdifferentiallymethylatedregionsincancerwithrockermeth AT ileniamigliaccio chartingdifferentiallymethylatedregionsincancerwithrockermeth AT lucamalorni chartingdifferentiallymethylatedregionsincancerwithrockermeth AT francescademichelis chartingdifferentiallymethylatedregionsincancerwithrockermeth
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Charting differentially methylated regions in cancer with Rocker-meth

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