Author

Irene S. L. Zeng

University of AucklandORCID 0000-0001-8100-3120Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Organism:human· 1 Assay:proteomics· 1

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Katya RuggieroliD· 1 shared Martin MiddleditchiD· 1 shared Thomas LumleyiD· 1 shared

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2017-2017 · peak 1/yr

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1 shared paperBioinformatics

Katya RuggierolORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJun 21, 2017

A Bayesian approach to multivariate and multilevel modelling with non-random missingness for hierarchical clinical proteomics data

Irene S. L. Zeng, Thomas Lumley, Katya Ruggierol, Martin Middleditch

The paper introduces a Bayesian multivariate multilevel model to analyze hierarchical clinical proteomics data with non-random missingness, showing improved performance over existing methods.

2 citations

humanproteomics

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