This GitHub project provides the code for the Patterning Scenario inference described in the chapter Modelling And Prediction of Patterning Phenomena On Drosophila Embryo (non published).

Python: Packages Z3 (SMT solver) and igraph (GRN visualization).

For Debian Linux:

sudo apt install python-pip

sudo python -m pip install z3-solver

sudo python -m pip install python-igraph

• models Example models.

• Python Contains the code for the Patterning Scenario inference approach.

• R Contains code related to the transformation of results from Boolean network inference (see repository regulomics/expansion-network for more information) into the syntax expected in the observations file.

Please refer to the report for more information about the implementation. Examples of input files can be found in folder models. Drosophila gap-gene segmentation model can be found in the following paper: Sanchez, L., & Thieffry, D. (2001). A logical analysis of the Drosophila gap-gene system. Journal of theoretical Biology, 211(2), 115-141.

To test function named function in the code, type in the terminal (in the "Python" folder):

python tests.py function

To see the list of avaiable tests, type the following command:

python tests.py

Tree structure of the model file associated with model named model:

- /
-- models/
--- model/
---- model.net
---- observations.spec

Experiments file is observations.spec, model file is called model.net.

python solve.py run model [--plot]

• Option --plot plots the gene concentration for each field (per plot), for each time step.

Example: To test the toy model provided, and plot the protein concentrations, type the following command:

python solve.py run toy --plot

If one wants to confront a given Patterning Scenario with a new initial state, and to generate trajectories with this selection of patterning functions, type the following:

python solve.py predict toy [--q0 InitialCondition] [--GRN InitialGRN] [--plot 0 or 1]

where phenotype (resp. GRN) associated with InitialCondition (resp. InitialGRN) is defined in the observations file. Argument for --plot is 1 (if concentration plots should be produced), otherwise 0.

Clémence Réda, 2018