Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies

The molecular basis of Alzheimer’s Disease has been obscured by heterogeneity and scarcity of brain gene expression data, which limit effectiveness in complex models. Here, the authors introduce a multi-task deep learning framework to learn generalizable and nuanced relationships between gene expres...

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Autores principales:	Nicasia Beebe-Wang, Safiye Celik, Ethan Weinberger, Pascal Sturmfels, Philip L. De Jager, Sara Mostafavi, Su-In Lee
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/d78ddb707ec94c1ab887dc583c8632d4
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spelling	oai:doaj.org-article:d78ddb707ec94c1ab887dc583c8632d42021-12-02T19:12:27ZUnified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies10.1038/s41467-021-25680-72041-1723https://doaj.org/article/d78ddb707ec94c1ab887dc583c8632d42021-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25680-7https://doaj.org/toc/2041-1723The molecular basis of Alzheimer’s Disease has been obscured by heterogeneity and scarcity of brain gene expression data, which limit effectiveness in complex models. Here, the authors introduce a multi-task deep learning framework to learn generalizable and nuanced relationships between gene expression and neuropathology.Nicasia Beebe-WangSafiye CelikEthan WeinbergerPascal SturmfelsPhilip L. De JagerSara MostafaviSu-In LeeNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Nicasia Beebe-Wang Safiye Celik Ethan Weinberger Pascal Sturmfels Philip L. De Jager Sara Mostafavi Su-In Lee Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
description	The molecular basis of Alzheimer’s Disease has been obscured by heterogeneity and scarcity of brain gene expression data, which limit effectiveness in complex models. Here, the authors introduce a multi-task deep learning framework to learn generalizable and nuanced relationships between gene expression and neuropathology.
format	article
author	Nicasia Beebe-Wang Safiye Celik Ethan Weinberger Pascal Sturmfels Philip L. De Jager Sara Mostafavi Su-In Lee
author_facet	Nicasia Beebe-Wang Safiye Celik Ethan Weinberger Pascal Sturmfels Philip L. De Jager Sara Mostafavi Su-In Lee
author_sort	Nicasia Beebe-Wang
title	Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
title_short	Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
title_full	Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
title_fullStr	Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
title_full_unstemmed	Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies
title_sort	unified ai framework to uncover deep interrelationships between gene expression and alzheimer’s disease neuropathologies
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d78ddb707ec94c1ab887dc583c8632d4
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Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies

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