Author

Alexandre Theodore Charles Bouillon

Vrije Universiteit BrusselORCID 0009-0006-0909-9694Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

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Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Organism:yeast· 1

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Johann LottermoseriD· 1 shared Jürgen ZanghelliniiD· 1 shared Leopold ZehetneriD· 1 shared María José Rimón MartíneziD· 1 shared Wim VrankeniD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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1 shared paperBioinformatics

Johann LottermoserORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintSep 3, 2026

Beyond benchmark accuracy: machine-learning turnover-number predictors require system-level validation

María José Rimón Martínez, Johann Lottermoser, Alexandre Theodore Charles Bouillon…·Jürgen Zanghellini

The paper evaluates machine learning predictors of enzyme turnover numbers (kcat) by testing their impact on downstream metabolic models, finding that accuracy varies significantly and that validation must consider system-level effects.

DOI 10.64898/2026.08.28.747816

yeastmachine learning (classical)

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