Nina Alperovich

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

The paper introduces GROQ-seq, a high-throughput platform for linking protein function to sequencing data, and presents pilot datasets for transcription factors, polymerases, and proteases.

Mapping the phenotypic landscape of a transcriptional repressor using Deep Mutational Scanning and Growth-based Quantitative Sequencing

The paper uses Deep Mutational Scanning and Growth-based Quantitative Sequencing to analyze CymR variants and identify amino acids essential for repressor function and mutations that improve ligand sensitivity.

Genetically encoded RNA strand exchange circuits for programmable protein expression and computation in cells

This study demonstrates genetically encoded RNA strand exchange circuits in living cells, showing that in vitro TMSE design principles apply to E. coli but with cellular-specific caveats.

Prevention of ribozyme catalysis through cDNA synthesis enables accurate RT-qPCR measurements of context-dependent ribozyme activity

The paper develops an RT-qPCR method to accurately measure context-dependent ribozyme activity by inhibiting cleavage during cDNA synthesis.

Precision engineering of biological function with large-scale measurements and machine learning

The paper presents two methods for precision engineering of genetic sensors using large-scale data and machine learning to achieve quantitative dose-response specifications.

A simple method for in situ, multiplexed measurement of RNA degradation by flow cytometry

This paper introduces a flow-FISH assay for high-throughput, in situ measurement of RNA degradation rates without RNA purification.

The genotype-phenotype landscape of an allosteric protein

Dose-response curves for 62 472 LacI coding sequences train a recurrent network for EC50 and G∞, enable EC50 targeting within 1.25-fold, and reveal band-stop sensors.