  The extraction of Compton Form Factors (CFFs) in a global analysis of almost
all Deeply Virtual Compton Scattering (DVCS) proton data is presented. The
extracted quantities are DVCS sub-amplitudes and the most basic observables
which are unambiguously accessible from this process. The parameterizations of
CFFs are constructed utilizing the artificial neural network technique allowing
for an important reduction of model dependency. The analysis consists of such
elements as feasibility studies, training of neural networks with the genetic
algorithm and a careful regularization to avoid over-fitting. The propagation
of experimental uncertainties to extracted quantities is done with the replica
method. The resulting parameterizations of CFFs are used to determine the
subtraction constant through dispersion relations. The analysis is done within
the PARTONS framework.
