What is UPMaBoSS

UPMaBoSS computes the evolution and the dynamics of a population of cells taking into account both their intracellular and intercellular regulations.

Simulations with UPMaBoSS are based on a logical model describing the intracellular regulations (logical regulatory graph complemented with logical rules), taking into account cell death, cell division, and intercellular communications.

The logical model of an individual cell is described as a MaBoSS model. At predefined intervals, the simulation of the cell population is stopped and the status of each cell of the population is updated according to the value of the variables representing cell death and cell division, and the value of the variables accounting for the activation or inhibition of signals coming from other cells. The simulation is then continued with the updated conditions until the maximum simulation time is reached. Since MaBoSS results are probabilistic, the simulation outputs of UpPMaBoSS can be interpreted as the behaviour of a cell population.

To run UPMaBoSS, three files are needed: a model file (in BND format), a configuration file with the transition rates, the simulation parameters and the initial conditions (in CFG format), and a file defining the update parameters (in UPP format).


How to run the jupyter notebooks

Run with Binder

Binder

Run docker locally

    docker run -p 8888:8888 -d sysbiocurie/upmaboss
Then open a browser at the following url : http://localhost:8888/tree/UPMaBoSS/

Run with conda locally

    git clone https://github.com/sysbio-curie/UPMaBoSS-docker.git
    conda create -n umb -c colomoto -c potassco pymaboss ginsim-python notebook seaborn
    conda activate umb
    jupyter notebook
Then open a browser at the following url : http://localhost:8888/tree/UPMaBoSS-docker/

Files for UPMaBoSS tutorials

Files for the toy model example

Jupyter notebook file
ToyModelUP.ipynb

Model files
ToyModelUP.bnd
ToyModelUP.cfg
ToyModelUP.upp

Jupyter notebook file describing how to build a upmaboss model from a qualitative model:
qualitative_to_upmaboss.ipynb


Files for the TNF example

Jupyter notebook file
CellFateModel_uppmaboss.ipynb

Model files
CellFateModel_uppmaboss.bnd
CellFateModel_uppmaboss.cfg
CellFateModel_uppmaboss.upp

Jupyter notebook file for Time Step Sensitivity Analysis:
TimeStepDependency.ipynb