Author

Thomas F. Knight

Ginkgo Bioworks, Inc. (United States)ORCID 0000-0002-6403-3480Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Synthetic Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Ahmed El-KishkyiD· 1 shared Alexus A. Smith· 1 shared Alicia Byrn· 1 shared Alvaro R. Bautista-AyalaiD· 1 shared Alycia Wong· 1 shared Alyssa Tran· 1 shared Andrew L. Consiglio· 1 shared Andrew Nesson· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperSynthetic Biology

Ahmed El-KishkyORCID

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2 papers

Recent·Most cited

Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis

Alexus A. Smith, Edmund L. Wong, Ronan C. Donovan, Brad Chapman, Ryan Harry, Pooyan Tirandazi, Paulina Kanigowska, Elizabeth A. Gendreau, Robert H. Dahl, Michal Jastrzebski, Jose E. Cortez, Christopher Bremner, José C. Morales Hemuda, James Dooner, Ian Graves, , Reshma P. Shetty

This paper demonstrates an LLM-driven autonomous lab that reduces the cost of cell-free protein synthesis by 40% and increases titer by 27% through iterative optimization.

bioRxiv · Feb 5, 2026 · PreprintSynthetic Biology

Optimization of Golden Gate assembly through application of ligation sequence-dependent fidelity and bias profiling

Vladimir Potapov, Jennifer L. Ong, Rebecca B. Kucera, Bradley W. Langhorst, Katharina Bilotti, John M. Pryor, Eric J. Cantor, Barry Canton, Thomas F. Knight, Thomas C. Evans, Gregory J. S. Lohman

The paper develops a method to optimize Golden Gate assembly by profiling ligation fidelity and bias, enabling efficient assembly of up to 24 fragments in a single reaction.

ACS Synthetic Biology · Oct 18, 2018Peer-reviewedSynthetic Biology