Author

John Spaeth

MIT Lincoln Laboratory

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

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Research Focus:protein design· 1 Assay:proteomics· 1

Frequent Co-Authors

Emily Engelhart· 1 shared Esther Gupta· 1 shared Leslie ShingiD· 1 shared Lin LiiD· 1 shared Matthew WalshiD· 1 shared Rafael JaimesiD· 1 shared Rajmonda S. CaceresiD· 1 shared Randolph M. Lopez· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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1 shared paperBioinformatics

Emily Engelhart

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1 paper

Recent·Most cited

Machine Learning Optimization of Candidate Antibodies Yields Highly Diverse Sub-nanomolar Affinity Antibody Libraries

Lin Li, Esther Gupta, John Spaeth, Leslie Shing, Rafael Jaimes, Emily Engelhart, Randolph M. Lopez, Rajmonda S. Caceres, Tristan Bepler, Matthew Walsh

This paper uses a Bayesian language model to design high-affinity scFv antibody libraries, achieving 28.8-fold better binding than directed evolution.

Nature Communications · Jun 12, 2023Peer-reviewedBioinformatics