Author

Rodrigo Cossio-Pérez

University College DublinORCID 0000-0002-4407-7179Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:benchmark study· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1 Research Focus:software / tool· 1

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Clement AgoniiD· 1 shared Denis C. ShieldsiD· 1 shared Hoang Thanh Lam· 1 shared Raúl Fernández-DíaziD· 1 shared Vanessa LópeziD· 1 shared

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2024-2024 · peak 1/yr

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1 shared paperBioinformatics

Clement AgoniORCID

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1 paper

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedSep 1, 2024

AutoPeptideML: A study on how to build more trustworthy peptide bioactivity predictors

Raúl Fernández-Díaz, Rodrigo Cossio-Pérez, Clement Agoni…·Denis C. Shields

This paper develops AutoPeptideML, an AutoML tool for peptide bioactivity prediction, showing that automated methods can improve model trustworthiness and efficiency.

34 citationstop 3%

proteomicsmachine learning (classical)

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