ArticleCommunications biology2021
Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals.
Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Temperature-Dependent Recombinase-Based Genetic Circuits.International journal of molecular sciences · 2025Article
- Engineering Inducible Cell Fate Transitions by Harnessing Epigenetic Silencing.bioRxiv : the preprint server for biology · 2025Article
- DOSE-L1000-Viz: an interactive Shiny application for dose-response transcriptomic analysis, target-centric exploration, and signature search.Bioinformatics (Oxford, England) · 2025Article
- DOSE-L1000: unveiling the intricate landscape of compound-induced transcriptional changes.Bioinformatics (Oxford, England) · 2023Article
- Functional Synthetic Biology.Synthetic biology (Oxford, England) · 2023Review
- Small molecule-inducible gene regulatory systems in mammalian cells: progress and design principles.Current opinion in biotechnology · 2022Review
- Building the Plant SynBio Toolbox through Combinatorial Analysis of DNA Regulatory Elements.ACS synthetic biology · 2022Article
- Engineering digitizer circuits for chemical and genetic screens in human cells.Nature communications · 2021Article
- Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals.Communications biology · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Many synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals. Using a combination of signal-to-noise ratio (SNR), area under a receiver operating characteristic curve (AUC), and fold change (FC), we evaluate three small-molecule inducible digitizer designs demonstrating FC up to 508x and SNR up to 3.77 dB. To study their behavior further and improve modularity, we develop a mixed phenotypic/mechanistic model capable of predicting digitizer configurations that amplify a synNotch cell-to-cell communication signal (Δ SNR up to 2.8 dB). We hope the metrics and modeling approaches here will facilitate incorporation of these digitizers into other systems while providing an improved workflow for gene circuit characterization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.