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Related Experiment Video

Updated: Feb 14, 2026

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions
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Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data.

Soumya Kannan1, Thomas Sams2, Jérôme Maury3

  • 1Department of Biotechnology and Biomedicine , Technical University of Denmark , 2800 Lyngby , Denmark.

ACS Synthetic Biology
|February 20, 2018
PubMed
Summary
This summary is machine-generated.

We developed PromAct, a new method using ordinary differential equations to accurately measure dynamic promoter activity. This system robustly estimates gene expression changes without inducers, improving systems biology and metabolic engineering.

Keywords:
dynamic modelfluorescent proteinsgrowth profilingordinary differential equationspromoter activity

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Area of Science:

  • Systems biology
  • Metabolic engineering
  • Synthetic biology

Background:

  • Accurate promoter activity characterization is crucial for designing biological expression systems.
  • Environmental responsiveness offers dynamic gene control without chemical inducers.
  • Estimating dynamic promoter activity is challenging due to indirect reporter gene measurements.

Purpose of the Study:

  • To develop a robust method for estimating dynamic promoter activity.
  • To improve the accuracy of promoter activity inference, especially for environmentally responsive promoters.
  • To provide a quantitative approach for analyzing dynamic gene expression data.

Main Methods:

  • Developed a system of ordinary differential equations (ODEs) for promoter activity inference.
  • The method, termed inference of dynamic promoter activity (PromAct), is robust to noise and growth rate variations.
  • Applied PromAct to quantitative datasets for estimating promoter activity rates.

Main Results:

  • PromAct accurately infers known promoter activity profiles.
  • The method correctly estimates the scale of promoter activity.
  • Demonstrated PromAct's capability to quantify dynamic promoter rates from experimental data.

Conclusions:

  • PromAct offers a robust and accurate method for estimating dynamic promoter activity.
  • This approach enhances the design and application of responsive biological systems.
  • Enables more precise quantitative analysis of gene expression in systems biology and metabolic engineering.