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danielebizzarri
MiMIR:Metabolomics-Based Models for Imputing Risk
Provides an intuitive framework for ad-hoc statistical analysis of 1H-NMR metabolomics by Nightingale Health. It allows to easily explore new metabolomics measurements assayed by Nightingale Health, comparing the distributions with a large Consortium (BBMRI-nl); project previously published metabolic scores [<doi:10.1016/j.ebiom.2021.103764>, <doi:10.1161/CIRCGEN.119.002610>, <doi:10.1038/s41467-019-11311-9>, <doi:10.7554/eLife.63033>, <doi:10.1161/CIRCULATIONAHA.114.013116>, <doi:10.1007/s00125-019-05001-w>]; and calibrate the metabolic surrogate values to a desired dataset.
Maintained by Daniele Bizzarri. Last updated 2 years ago.
binary-risk-factorsbiomarkerslinear-regressionmetabolitesmetabolomicsnightingale-metabolomicsrisk-factor-modelsrisk-factorssurrogate-models
8 stars 4.11 score 32 scripts