Author

Otto I. Savolainen

Chalmers University of TechnologyORCID 0000-0002-7063-5525Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Aleksej ZelezniakiD· 1 shared Audrius LaurynėnasiD· 1 shared Donatas RepeckaiD· 1 shared Elzbieta RembezaiD· 1 shared Irmantas Rokaitis· 1 shared Jan ZrimeciD· 1 shared Laurynas KarpusiD· 1 shared Martin K. M. EngqvistiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperSynthetic Biology

Aleksej ZelezniakORCID

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1 paper

Recent·Most cited

Expanding functional protein sequence space using generative adversarial networks

Donatas Repecka, Vykintas Jauniškis, Laurynas Karpus, Elzbieta Rembeza, Irmantas Rokaitis, Jan Zrimec, Simona Povilonienė, Audrius Laurynėnas, Sandra Viknander, Wissam Abuajwa, Otto I. Savolainen, Rolandas Meškys, Martin K. M. Engqvist, Aleksej Zelezniak

This paper introduces ProteinGAN, a GAN that generates functional protein sequences, showing 24% of generated sequences are soluble and active in vitro.

Nature Machine Intelligence · Mar 4, 2021Peer-reviewedSynthetic Biology