An evolutionary procedure for inferring MP systems regulation functions of
biological networks

Alberto Castellini, Vincenzo Manca and Mauro Zucchelli

Natural Computing

This webpage presents supplementary material and comparison between results proposed in the current paper (called CastelliniEtAl2013 in the following) and results proposed in CastelliniEtAl2012.

References:

CastelliniEtAl2012: A. Castellini, V. Manca, and M. Zucchelli. Towards an evolutionary procedure for reverse-engineering biological networks. LNCS 7597, pages 271-285. Springer, 2012.

CastelliniEtAl2013: A. Castellini, V. Manca, and M. Zucchelli. An evolutionary procedure for inferring MP systems regulation functions of biological networks. Natural Computing. Submitted.

 

Simulation errors, number of regressors and negative-flux errors

Comparison between the target dynamics (circles) and the dynamics generated using the synthesized regulation functions (crosses).

Flux time series

 

 

 

 

 

 

Heat maps for regulation functions

Columns represent primitive functions, rows represent single tests (i.e., experiments) of the evolutionary procedure. Cell i,j is colored from blue to red according to the coefficient assigned to the j-th primitive function in the i-th experiment.

 

Statistical analysis of regressor coefficients (for regulation functions)

For each regressor (row) and regulation function (column) it is reported the number of tests in which the regressor has been selected for this regulation function (# sel) and the mean and standard deviation of coefficients assigned to that regressor (mu/sigma).

Heat maps for substances

Columns represent primitive functions, rows represent single tests of the evolutionary procedure. Cell i,j is colored from blue to red according to the sum of coefficients assigned to the j-th primitive function by all the regulation functions which directly affect the substance, in the i-th test of the evolutionary procedure.

Statistical analysis of regressor coefficients (for substances)

For each regressor (row) and substance (column) it is reported the number of tests in which the regressor has been selected in a regulation function which directly influences that substance concentration (# sel) and the mean and standard deviation of the sum of coefficients assigned to that regressor in a regulation function which directly influences that substance concentration (mu/sigma).