Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements

Identifying gene subsets affecting disease phenotypes from transcriptome data is challenge. Here, the authors develop a method that combines transcriptional data with disease ordinal clinical measurements to discover a sphingolipid metabolism regulator involving in Huntington’s disease progression....

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Autores principales: Leila Pirhaji, Pamela Milani, Simona Dalin, Brook T. Wassie, Denise E. Dunn, Robert J. Fenster, Julian Avila-Pacheco, Paul Greengard, Clary B. Clish, Myriam Heiman, Donald C. Lo, Ernest Fraenkel
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Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/ec0af8273fb342fcbf9ccadba0111a01
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spelling oai:doaj.org-article:ec0af8273fb342fcbf9ccadba0111a012021-12-02T14:40:57ZIdentifying therapeutic targets by combining transcriptional data with ordinal clinical measurements10.1038/s41467-017-00353-62041-1723https://doaj.org/article/ec0af8273fb342fcbf9ccadba0111a012017-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-00353-6https://doaj.org/toc/2041-1723Identifying gene subsets affecting disease phenotypes from transcriptome data is challenge. Here, the authors develop a method that combines transcriptional data with disease ordinal clinical measurements to discover a sphingolipid metabolism regulator involving in Huntington’s disease progression.Leila PirhajiPamela MilaniSimona DalinBrook T. WassieDenise E. DunnRobert J. FensterJulian Avila-PachecoPaul GreengardClary B. ClishMyriam HeimanDonald C. LoErnest FraenkelNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-13 (2017)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Leila Pirhaji
Pamela Milani
Simona Dalin
Brook T. Wassie
Denise E. Dunn
Robert J. Fenster
Julian Avila-Pacheco
Paul Greengard
Clary B. Clish
Myriam Heiman
Donald C. Lo
Ernest Fraenkel
Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
description Identifying gene subsets affecting disease phenotypes from transcriptome data is challenge. Here, the authors develop a method that combines transcriptional data with disease ordinal clinical measurements to discover a sphingolipid metabolism regulator involving in Huntington’s disease progression.
format article
author Leila Pirhaji
Pamela Milani
Simona Dalin
Brook T. Wassie
Denise E. Dunn
Robert J. Fenster
Julian Avila-Pacheco
Paul Greengard
Clary B. Clish
Myriam Heiman
Donald C. Lo
Ernest Fraenkel
author_facet Leila Pirhaji
Pamela Milani
Simona Dalin
Brook T. Wassie
Denise E. Dunn
Robert J. Fenster
Julian Avila-Pacheco
Paul Greengard
Clary B. Clish
Myriam Heiman
Donald C. Lo
Ernest Fraenkel
author_sort Leila Pirhaji
title Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
title_short Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
title_full Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
title_fullStr Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
title_full_unstemmed Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
title_sort identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements
publisher Nature Portfolio
publishDate 2017
url https://doaj.org/article/ec0af8273fb342fcbf9ccadba0111a01
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