  We present the first NNPDF full set of Parton Distribution Functions from a
comprehensive DIS analysis. This approach, combining a Monte Carlo sampling of
the probability measure in the space of PDFs with the use of neural networks as
interpolating functions, provides a faithful and statistically sound
determination of the uncertainty in parton distributions. The features of the
fit and the results are discussed in details as well as some preliminary
phenomenological analysis
