  We present recent results of the NNPDF collaboration on a full DIS analysis
of Parton Distribution Functions (PDFs). Our method is based on the idea of
combining a Monte Carlo sampling of the probability measure in the space of
PDFs with the use of neural networks as unbiased universal interpolating
functions. The general structure of the project and the features of the fit are
described and compared to those of the traditional approaches.
