English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Genetic circuits are designed to implement certain logic in living cells,keeping burden on the host cell minimal. However, manipulating the genome oftenwill have a significant impact for various reasons (usage of the cell machineryto express new genes, toxicity of genes, interactions with native genes, etc.).In this work we utilize Koopman operator theory to construct data-driven modelsof transcriptomic-level dynamics from noisy and temporally sparse RNAseqmeasurements. We show how Koopman models can be used to quantify impact ongenetic circuits. We consider an experimental example, using high-throughputRNAseq measurements collected from wild-type E. coli, single gate componentstransformed in E. coli, and a NAND circuit composed from individual gates in E.coli, to explore how Koopman subspace functions encode increasing circuitinterference on E. coli chassis dynamics. The algorithm provides a novel methodfor quantifying the impact of synthetic biological circuits on host-chassisdynamics.

A data-driven method for quantifying the impact of a genetic circuit on its host