The geometry of clinical labs and wellness states from deeply phenotyped humans

Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. Here, the authors apply Pareto Task Inference to analyze the clinical lab tests of 3094 individuals and find three wellness states, and one aberrant health state defining this cohort...

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Autores principales:	Anat Zimmer, Yael Korem, Noa Rappaport, Tomasz Wilmanski, Priyanka Baloni, Kathleen Jade, Max Robinson, Andrew T. Magis, Jennifer Lovejoy, Sean M. Gibbons, Leroy Hood, Nathan D. Price
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3bc217cadb6347bdb67f294b25377a9c
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spelling	oai:doaj.org-article:3bc217cadb6347bdb67f294b25377a9c2021-12-02T18:06:34ZThe geometry of clinical labs and wellness states from deeply phenotyped humans10.1038/s41467-021-23849-82041-1723https://doaj.org/article/3bc217cadb6347bdb67f294b25377a9c2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23849-8https://doaj.org/toc/2041-1723Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. Here, the authors apply Pareto Task Inference to analyze the clinical lab tests of 3094 individuals and find three wellness states, and one aberrant health state defining this cohort.Anat ZimmerYael KoremNoa RappaportTomasz WilmanskiPriyanka BaloniKathleen JadeMax RobinsonAndrew T. MagisJennifer LovejoySean M. GibbonsLeroy HoodNathan D. PriceNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Anat Zimmer Yael Korem Noa Rappaport Tomasz Wilmanski Priyanka Baloni Kathleen Jade Max Robinson Andrew T. Magis Jennifer Lovejoy Sean M. Gibbons Leroy Hood Nathan D. Price The geometry of clinical labs and wellness states from deeply phenotyped humans
description	Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. Here, the authors apply Pareto Task Inference to analyze the clinical lab tests of 3094 individuals and find three wellness states, and one aberrant health state defining this cohort.
format	article
author	Anat Zimmer Yael Korem Noa Rappaport Tomasz Wilmanski Priyanka Baloni Kathleen Jade Max Robinson Andrew T. Magis Jennifer Lovejoy Sean M. Gibbons Leroy Hood Nathan D. Price
author_facet	Anat Zimmer Yael Korem Noa Rappaport Tomasz Wilmanski Priyanka Baloni Kathleen Jade Max Robinson Andrew T. Magis Jennifer Lovejoy Sean M. Gibbons Leroy Hood Nathan D. Price
author_sort	Anat Zimmer
title	The geometry of clinical labs and wellness states from deeply phenotyped humans
title_short	The geometry of clinical labs and wellness states from deeply phenotyped humans
title_full	The geometry of clinical labs and wellness states from deeply phenotyped humans
title_fullStr	The geometry of clinical labs and wellness states from deeply phenotyped humans
title_full_unstemmed	The geometry of clinical labs and wellness states from deeply phenotyped humans
title_sort	geometry of clinical labs and wellness states from deeply phenotyped humans
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3bc217cadb6347bdb67f294b25377a9c
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The geometry of clinical labs and wellness states from deeply phenotyped humans

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