Author

Irmantas Rokaitis

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Synthetic Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

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 Jan ZrimeciD· 1 shared Laurynas KarpusiD· 1 shared Martin K. M. EngqvistiD· 1 shared Otto I. SavolaineniD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperSynthetic Biology

Aleksej ZelezniakORCID

Mutual co-authors in cluster

Author profile →

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