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Svetlana Ikonomova (Fed)

Svetlana Ikonomova is research scientist in the Cellular Engineering Group at NIST. Her current focus is on large-scale measurements of genotype-phenotype landscapes in bacteria and yeast. 

Svetlana has used her protein engineering background to engineer and study targets of different sizes. She first joined NIST as part of Biomolecular Structure and Function Group, where she engineered a protein to enhance its binding affinity to N-terminal amino acid for use in next-generation protein sequencing platform. Before joining NIST, Svetlana studied the assembly mechanism of bacterial microcompartments in Salmonella enterica as a postdoctoral fellow at Northwestern University. During her graduate studies, she used rational design on antifungal peptide to improve its antifungal activity and increase its proteolytic resistance against proteases secreted by Candida albicans.

Publications

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Publications

GROQ-seq Datasets Across Transcription Factors (LacI, RamR, VanR), T7 RNA Polymerase and TEV Protease

Author(s)
Aviv Spinner, Shwetha Sreenivasan, James McLellan, Svetlana Ikonomova, Dana Cortade, Simon d'Oelsnitz, Kristen Sheldon, Olga Vasilyeva, Nina Alperovich, Anjali Chadha, Lily Nematollahi, Andi Dhroso, Zach Sisson, Corey Hudson, Erika DeBenedictis, Peter Kelly, Amanda Reider Apel, David Ross, Catherine Baranowski
Predicting any protein's function from its sequence alone would be a significant breakthrough in molecular biology. Although machine learning approaches have...

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

Author(s)
Svetlana Ikonomova, Bruce Wittmann, Fernanda Piorino Macruz de Oliveira, David Ross, Samuel Schaffter, Olga Vasilyeva, Elizabeth Strychalski, Eric Horvitz, James Diggans, Sheng Lin-Gibson, Geoffrey Taghon
Advances in machine learning are providing new abilities for engineering biology, promising leaps forward with beneficial applications. At the same time, these...
Created July 29, 2021, Updated December 19, 2025
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