In silico data-set used to train the PGNNIV

The folder contains the data used to train PGNNIVs to unravel the go or grow behaviour of glioblastoma under 4 different parametric models. These data consist on the solutions (in time and space) of eleven simulations with different oxygen boundary conditions.

Each folder is named as DATA_"ModelName", where "ModelName" can be: "Sigmoid", "ReLU", "MichaelisMenten" or "Heaviside". Inside each folder, the multidimensional arrays for input and output data for the network training can be found. These arrays have dimension [nExp,TimeStep,x,field], where:

• nExp = 11  and corresponds to the number of different configurations or experiments simulated.
• TimeStep = 1000 and correspond to the different temporal frames where the solution is given.
• x = 51 and corresponds to the different spatial points where the solution is given.
• field = 2 and correspond to the different solution fields (1: cells, 2: oxygen).