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Machine learning identifies regulatory changes in the lung as key to the conversion of genetic risk to Type 1 diabetes

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posted on 2020-10-15, 07:36 authored by Denis NyagaDenis Nyaga, Daniel HoDaniel Ho, William SchierdingWilliam Schierding, Richard SafferyRichard Saffery, Mark VickersMark Vickers, Jo PerryJo Perry, Andreas Kempa-LiehrAndreas Kempa-Liehr, Justin O'SullivanJustin O'Sullivan

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University of Auckland

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justin.osullivan@auckland.ac.nz

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Keywords

Type 1 diabetes genetic architecture machine learning-based Immune Cell Association Functional genomics analysis expression quantitative trait loci analysis Genomics Genome Structure and Regulation Epigenetics (incl. Genome Methylation and Epigenomics)

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