Author

Steffen Schmidt

University of BayreuthORCID 0000-0001-9077-6010Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biochemistry· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1 Approach:large language model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Birte HöckeriD· 2 shared Noelia FerruziD· 2 shared Alexander E. BrauniD· 1 shared Sergio Romero‐RomeroiD· 1 shared Timo Kossendey· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBiochemistry

Birte HöckerORCID

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintNov 10, 2024

De novo design of triosephosphate isomerases using generative language models

Sergio Romero‐Romero, Alexander E. Braun, Timo Kossendey…·Birte Höcker

This study uses generative language models to design de novo triosephosphate isomerases, which show catalytic activity in E. coli.

11 citations

E. coliprotein sequence

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BioinformaticsNature CommunicationsPeer-reviewedJul 27, 2022

A deep unsupervised language model for protein design

Noelia Ferruz, Steffen Schmidt, Birte Höcker

This paper introduces ProtGPT2, a deep unsupervised language model for protein design that generates de novo protein sequences with properties similar to natural proteins.

797 citationstop 1%

protein sequencedeep learning

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