First-principles prediction of the information processing capacity of a simple genetic circuit
Welcome to the GitHub repository for the channel capacity project! This repository serves as a record for the experimental and theoretical work described in the publication "First-principles prediction of the information processing capacity of a simple genetic circuit"
This repository contains two main branches --
master which you are reading right now is the primary branch for the
project. In here you will find all of the polished and unpolished code used for
all the calculations and figure generation in the paper. The
contains all of the website files.
What the branch
master does not contain are the data files for the project.
But you can download such datasets from the links in the website.
Please see individual directories for more information.
The intend of this repository is to make every step of the publication
completely transparent and reproducible. The project involved a significant
amount of home-grown Python code that we wrapped as a module
install the package first you need to make sure that you have all of the
required dependencies. To check for this you can use
pip by executing the following command:
pip install -r requirements.txt
Once you have all of the packages installed locally, you can install our custom module by running the following command:
pip install -e ./
When installed, a new folder
ccutils.egg-info will be installed. This folder
is required for the executing of the code in this repository.
For convenience the repository is divided into several directories and subdirectories. Please see each directory for information regarding each file.
This folder contains all the source code used for the project. From the processing of the raw microscopy images, to the generation of all figures. The directory is broken up into the following subdirectories:
channcap_exp| contains the processing of all of the single-cell fluorescence data used to determine the experimental channel capacity of the different strains.
figs| contains all the scripts to reproduce every plot in the main text and in the supplementary material.
image_analysis| contains scripts used to process the raw microscopy images in order to segment the cells and extract single-cell fluorescence values.
theory| contains Jupyter notebooks and scripts for all theoretical calculations in the paper. From symbolic computations using
sympy, to numerical integration of dynamical equations, to the approximation of distributions using the maximum entropy principle.
This folder contains templates for all the routine analysis used in the project. From the metadata file that goes along the microscopy images, to the analysis pipeline to extract single-cell fluorescence values.
This folder contains all the raw and processed data generated from the
experimental microscopy images as well as the numerical computations derived
from the theoretical model. Although not all of the content of this folder is
sync with the
GitHub repository, all the scripts require the following
structure in order for them to run accordingly. The raw data can be directly
downloaded from the
paper website where we
indicate in which of the following folders each of the datasets should be
csv_channcap_bootstrap[not sync] | This folder contains all of the experimental channel capacity inferences done on the single-cell microscopy data. These files can be downloaded here.
csv_gillespie[not sync] | This folder stores the output of the Gillespie simulations of the chemical master equation. The files can be directly generated by running the following jupyter notebook.
csv_maxEnt_dist| This folder contains three types of files:
- Values of mRNA and protein distributions as computed from integrating the moment equations.
- Value of the Lagrange multipliers needed to approximate the full molecule count distribution.
- Theoretically inferred channel capacity.
csv_microscopy| This folder contains the processed single-cell fluorescence intensities.
mRNA_FISH| This folder contains the single-molecule mRNA counts from Jones et al, 2014.
microscopy[not sync] | This folder contains all of the raw microscopy images. The files can be directly downloaded here.
All creative works (writing, figures, etc) are licensed under the Creative Commons CC-BY 4.0 license. All software is distributed under the standard MIT license as follows
Copyright 2020 The Authors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.