This repository contains code for effective synthetic circuit models written in the Julia programming language. The synthetic circuits and model equations are described in the publication:
Julia v1.3 or greater must be installed on your machine. In addition, the solution and analysis of the effective TX/TL models require a few additional packages:
| Package | Description |
|---|---|
| DifferentialEquations.jl | A suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R |
| DiffEqSensitivity.jl | Encodes sensitivity analysis utilities |
| JSON.jl | Package for parsing and printing JSON |
| Optim.jl | Univariate and multivariate optimization solvers |
| DataFrames.jl | Tools for working with tabular data in Julia |
| CSV.jl | Package for working with delimited files |
| Interpolations.jl | Package implements a variety of interpolation schemes for the Julia language |
| Distributions.jl | A Julia package for probability distributions and associated functions |
| PyPlot.jl | Julia interface to the Matplotlib plotting library from Python |
| POETs.jl | A Julia package that implements the Pareto Optimal Ensemble Techniques (POETs) method for multiobjective optimization |
These packages will be installed and compiled the first time you execute the model code (which can take a bit). If this doesn't happen, you can always install them using the Julia package manager. To get the model codes, you can download this model repository as a zip file, clone or pull it using the command:
git pull https://github.com/varnerlab/Biophysical-TXTL-Model-Code
or
git clone https://github.com/varnerlab/Biophysical-TXTL-Model-Code
In the src directory there are two subdirectories P70-deGFP-model and P28-cIssrA-model which contain
the code for the P70-deGFP model and the P28 negative feedback model.
Each model subdirectory contains scripts to solve or analyze the model equations:
| Script | Description |
|---|---|
sample_parameter_ensemble.jl |
Solves the model equations for the ensemble of parameters sets. Saves solutions in the simulations directory |
visualize_*.jl |
Plot the simulations generated by the sample_parameter_ensemble.jl script |
compute_sensitivity_coefficients.jl |
Conducts Morris sensitivity analysis on the model |