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RACIPE: a computational tool for modeling gene regulatory circuits using randomization.

Bin Huang1, Dongya Jia1,2, Jingchen Feng1

  • 1Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.

BMC Systems Biology
|June 20, 2018
PubMed
Summary
This summary is machine-generated.

A new computational tool, Random Circuit Perturbation (RACIPE), enables gene regulatory circuit analysis without needing kinetic parameters. This method explores robust dynamical features and gene functions in complex networks.

Keywords:
Dynamical featuresGRNsGene regulatory circuitsRACIPERandom circuit perturbationStatistical analysis

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Traditional mathematical modeling of gene regulatory circuits faces challenges due to insufficient kinetic parameter knowledge.
  • Parameter inference from experimental data or assumptions is time-consuming and error-prone, particularly for large networks.

Purpose of the Study:

  • To introduce a user-friendly computational tool for analyzing gene regulatory circuits.
  • To enable exploration of robust dynamical features without requiring detailed kinetic parameters.

Main Methods:

  • The Random Circuit Perturbation (RACIPE) method uses only network topology as input.
  • RACIPE generates an ensemble of circuit models with randomized parameters.
  • Statistical analysis identifies robust dynamical properties and gene expression patterns.

Main Results:

  • The study presents the implementation of the RACIPE software.
  • Methods for statistical analysis of RACIPE-generated data are discussed.
  • The tool was applied to coupled toggle-switch circuits and a B-lymphopoiesis circuit.

Conclusions:

  • The RACIPE computational tool offers a more comprehensive and unbiased understanding of gene regulatory network mechanisms.
  • RACIPE is a free, open-source software available on GitHub.