Author

Stefan Holderbach

Heidelberg UniversityORCID 0000-0002-0599-4716Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Organism:E. coli· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Adrian BachmanniD· 1 shared Ann-Sophie Helene KroelliD· 1 shared Benedict WolfiD· 1 shared Dominik NiopekiD· 1 shared Jan MathonyiD· 1 shared Joshua EigenmanniD· 1 shared Luca BrenkeriD· 1 shared Nicholas T. SoutherniD· 1 shared

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2024-2024 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperSynthetic Biology

Adrian BachmannORCID

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1 paper

Recent·Most cited

Rational engineering of allosteric protein switches by in silico prediction of domain insertion sites

Benedict Wolf, Pegi Shehu, Luca Brenker, Adrian Bachmann, Ann-Sophie Helene Kroell, Nicholas T. Southern, Stefan Holderbach, Joshua Eigenmann, Sabine Aschenbrenner, Jan Mathony, Dominik Niopek

This paper introduces ProDomino, a machine learning tool for predicting domain insertion sites in proteins, validated experimentally in E. coli and human cells to create opto- and chemogenetic switches.

bioRxiv · Dec 4, 2024 · PreprintSynthetic Biology