Author

Alina Peluso

Imperial College LondonORCID 0000-0003-2895-0406Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metabolomics· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Robert Charles GleniD· 2 shared Timothy M. D. EbbelsiD· 2 shared Alejandra N Gonzalez-BeltraniD· 1 shared Anders O. LarssoniD· 1 shared Antonio RosatoiD· 1 shared Bita KhaliliiD· 1 shared Carles FoguetiD· 1 shared Christian LudwigiD· 1 shared

Activity by Year

2018-2021 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Robert Charles GlenORCID

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2 papers

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedFeb 12, 2021

Estimation of permutation-based metabolome-wide significance thresholds

Alina Peluso, Robert Charles Glen, Timothy M. D. Ebbels

The paper estimates permutation-based metabolome-wide significance thresholds using parametric approximations and permutation procedures to control type I error rates in metabolome-wide association studies.

32 citations

metabolomicsstatistical model

𝕏 PostBluesky

BioinformaticsGigaSciencePeer-reviewedDec 7, 2018

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

Kristian Peters, James Bradbury, Sven Bergmann…·Christoph Steinbeck

PhenoMeNal provides a cloud-based platform for metabolomics data analysis, integrating tools and workflows to enable reproducible and scalable research.

150 citationstop 1%

metabolomicsstatistical model

𝕏 PostBluesky