TF_GA: Bacterial Promoter Modeling with Genetic Programming

This project aims at using Genetic Programming to evolve models of regulated bacterial promoters, using datasets of upstream sequences of genes known or suspected to be regulated by a common set of transcription factors, and a control dataset of non-regulated sequences.

A tree will be the data struture to save the models (organism). In this data structure we find two main types of nodes: connectors and PSSM-type recognizers.

• Connectors: node objects that connect up to parent node and down to two nodes. A connector has a specified ideal distance between its downstream connecting elements.
• PSSM-type recognizers: node objects that specify a short (e.g. 4-5 bp) DNA recognition pattern. Based on the BioPython motifs class.

Install with virtualenv

I personally use virtualenv from python to create the virtual environment.

First of all you need python3 and pip3 installed. Use ther version 3.7.3. Check everything is right running the following commands:

python3 -V
# Python 3.7.3

pip3 list
# List of packages installed

which python3
# /usr/bin/python3

which pip3
# /usr/local/bin/pip

Once you have everything installed, install virtualenv using pip:

pip3 install virtualenv

# and check it with 
which virtualenv

Now we can create the virtualenv, it will generate a directory with the new env:

virtualenv -p python3 TF_GA_env

#Activate the new env with:
source TF_GA_env/bin/activate

#Check the new env with:

python -V
# Python 3.7.3

pip list
# List of packages installed

which python
# /path/to/env/bin/python3

which pip
# /path/to/env/bin/pip

#Deactivate the new env with:
deactivate

And to install the necessary packages:

# pip install PACKAGE

Install with conda

If you are more confortable using conda you can import the env using the following YAML:

name: TF_GA_env_conda
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - biopython=1.76=py37h7b6447c_0
  - blas=1.0=mkl
  - ca-certificates=2020.1.1=0
  - certifi=2019.11.28=py37_0
  - intel-openmp=2020.0=166
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - mkl=2020.0=166
  - ncurses=6.1=he6710b0_1
  - numpy=1.11.3=py37h7e9f1db_12
  - numpy-base=1.11.3=py37hde5b4d6_12
  - openssl=1.1.1d=h7b6447c_4
  - pip=20.0.2=py37_1
  - python=3.7.3=h0371630_0
  - readline=7.0=h7b6447c_5
  - setuptools=45.2.0=py37_0
  - sqlite=3.31.1=h7b6447c_0
  - tk=8.6.8=hbc83047_0
  - wheel=0.34.2=py37_0
  - xz=5.2.4=h14c3975_4
  - zlib=1.2.11=h7b6447c_3

You can create it using the following command:

conda env create -f environment.yml

Generate documentation

To generate documentation we use the pdoc command (not installed by default).

# Move to the source dir
cd /path/to/project/src

# Generate the new docmentation
pdoc --html .

# Remove old documentation
rm -rf ../docs/html

# Move the new documentation to the docs dir
mv html/ ../docs/

Python related

Developing in Python 3.7.3

Libraries:

• BioPython 1.76
• numpy 1.11.3