GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.

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Autores principales:	Arno van Hilten, Steven A. Kushner, Manfred Kayser, M. Arfan Ikram, Hieab H. H. Adams, Caroline C. W. Klaver, Wiro J. Niessen, Gennady V. Roshchupkin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/204c0fb0a15742cb9761a666d57de397
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spelling	oai:doaj.org-article:204c0fb0a15742cb9761a666d57de3972021-12-02T17:25:42ZGenNet framework: interpretable deep learning for predicting phenotypes from genetic data10.1038/s42003-021-02622-z2399-3642https://doaj.org/article/204c0fb0a15742cb9761a666d57de3972021-09-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02622-zhttps://doaj.org/toc/2399-3642van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.Arno van HiltenSteven A. KushnerManfred KayserM. Arfan IkramHieab H. H. AdamsCaroline C. W. KlaverWiro J. NiessenGennady V. RoshchupkinNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Arno van Hilten Steven A. Kushner Manfred Kayser M. Arfan Ikram Hieab H. H. Adams Caroline C. W. Klaver Wiro J. Niessen Gennady V. Roshchupkin GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
description	van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.
format	article
author	Arno van Hilten Steven A. Kushner Manfred Kayser M. Arfan Ikram Hieab H. H. Adams Caroline C. W. Klaver Wiro J. Niessen Gennady V. Roshchupkin
author_facet	Arno van Hilten Steven A. Kushner Manfred Kayser M. Arfan Ikram Hieab H. H. Adams Caroline C. W. Klaver Wiro J. Niessen Gennady V. Roshchupkin
author_sort	Arno van Hilten
title	GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
title_short	GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
title_full	GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
title_fullStr	GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
title_full_unstemmed	GenNet framework: interpretable deep learning for predicting phenotypes from genetic data
title_sort	gennet framework: interpretable deep learning for predicting phenotypes from genetic data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/204c0fb0a15742cb9761a666d57de397
work_keys_str_mv	AT arnovanhilten gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT stevenakushner gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT manfredkayser gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT marfanikram gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT hieabhhadams gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT carolinecwklaver gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT wirojniessen gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata AT gennadyvroshchupkin gennetframeworkinterpretabledeeplearningforpredictingphenotypesfromgeneticdata
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GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

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