Author

Karin Felderer

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Biochemistry· 1

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Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1

Frequent Co-Authors

Daniel A. M. PaisiD· 1 shared Hitto Kaufmann· 1 shared Jan-Peter A. Mayer· 1 shared Maria B. BatalhaiD· 1 shared Raman KumariD· 1 shared Sandra Regina Augusta da SilvaiD· 1 shared Sofia T. Santos· 1 shared Timo Eichner· 1 shared

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2024-2024 · peak 1/yr

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1 shared paperBiochemistry

Daniel A. M. PaisORCID

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1 paper

Recent·Most cited

BiochemistryJournal of Computer-Aided Molecular DesignPeer-reviewedAug 20, 2024

Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors

Daniel A. M. Pais, Jan-Peter A. Mayer, Karin Felderer…·Hitto Kaufmann

This paper develops machine learning models to predict the developability of Anticalin proteins using sequence-based descriptors, achieving low prediction errors and validated through cross-validation.

1 citation

protein sequencemachine learning (classical)

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