Author

Dino Oglić

AstraZeneca (United Kingdom)ORCID 0000-0002-4728-9644Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:large language model· 1 Research Focus:protein design· 1

Frequent Co-Authors

Charlotte Mary DeaneiD· 2 shared Oliver M. TurnbulliD· 2 shared Rebecca Croasdale-WoodiD· 2 shared Ferran Gonzalez HernandeziD· 1 shared Lorena Roldán-MartíniD· 1 shared Maliha Sultana· 1 shared Rohan KumariD· 1 shared Tom DietheiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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2 shared papersSynthetic Biology

Charlotte Mary DeaneORCID

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2 papers

Recent·Most cited

Generative Language Modeling for Antibody CDR Grafting and Alignment-driven De Novo Design

Ferran Gonzalez Hernandez, Oliver M. Turnbull, Maliha Sultana, Lorena Roldán-Martín, Rohan Kumar, Tom Diethe, Rebecca Croasdale-Wood, Charlotte Mary Deane, Dino Oglić

GenCDR uses LLaMa-based models to generate antibody CDRs with framework context, achieving high recovery and developable designs through alignment-driven training.

bioRxiv · Sep 10, 2026 · PreprintSynthetic Biology

p-IgGen: A Paired Antibody Generative Language Model

Oliver M. Turnbull, Dino Oglić, Rebecca Croasdale-Wood, Charlotte Mary Deane

p-IgGen generates paired heavy-light chain antibodies with biophysical properties similar to clinical-stage therapeutics.

Bioinformatics · Nov 1, 2024Peer-reviewedImmunology