Author

Rahel Frick

Johns Hopkins UniversityORCID 0000-0002-3469-5686Unclaimed ORCID profile · follow to get notified of new preprints

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Rahel Frick1 paper

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Approach:contrastive learning· 1 Organism:human· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Daphné TruaniD· 1 shared Diego del AlamoiD· 1 shared Jeffrey A. RuffoloiD· 1 shared Jeffrey J. GrayiD· 1 shared Joel D. KarpiakiD· 1 shared Sai Pooja MahajaniD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 6 mutual co-author links

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1 shared paperBioengineering

Daphné TruanORCID

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2 papers

Recent·Most cited

Adapting ProteinMPNN for antibody design without retraining

Diego del Alamo, Rahel Frick, Daphné Truan, Joel D. Karpiak

This paper shows that combining ProteinMPNN with AbLang improves antibody design, generating more effective HER2 binders than ProteinMPNN alone.

bioRxiv · May 9, 2025 · PreprintBioengineering

Hallucinating structure-conditioned antibody libraries for target-specific binders

Sai Pooja Mahajan, Jeffrey A. Ruffolo, Rahel Frick, Jeffrey J. Gray

The paper introduces FvHallucinator, a deep learning model that generates antibody CDR libraries conditioned on structure, improving binding affinity and enriching for therapeutic candidates.

Frontiers in Immunology · Oct 21, 2022Peer-reviewedBioinformatics