Author

Laurie Prélot

ETH ZurichORCID 0000-0001-7063-5333Unclaimed ORCID profile · follow to get notified of new preprints

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Laurie Prélot1 paper

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Organism:human· 2 Approach:benchmark study· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

André KahlesiD· 1 shared Andy LiniD· 1 shared Beverley BalkauiD· 1 shared Gunnar RätschiD· 1 shared Harmen H. M. DraismaiD· 1 shared Inga ProkopenkoiD· 1 shared Julianne K. DavidiD· 1 shared Loïc YengoiD· 1 shared

Activity by Year

2018-2025 · peak 1/yr

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10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

André KahlesORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 10, 2025

Splicing neoepitope prediction is sensitive to methodological differences

Laurie Prélot, Julianne K. David, Andy Lin…·Gunnar Rätsch

The paper evaluates the impact of methodological differences on splicing neoepitope prediction, finding high variability and limited reproducibility across pipelines.

1 citation

humanbulk RNA-seq

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GenomicsbioRxivPreprintDec 13, 2018

Machine Learning in Multi-Omics Data to Assess Longitudinal Predictors of Glycaemic Health

Laurie Prélot, Harmen H. M. Draisma, Mila Desi Anasanti…·Inga Prokopenko

The paper uses machine learning to predict glycaemic traits from multi-omics data in longitudinal cohorts, identifying key predictors like methylation marks and metabolic variables.

8 citations

humanmetabolomics

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