  Protein interaction networks (PIN) are popular means to visualize the
proteome. However, PIN datasets are known to be noisy, incomplete and biased by
the experimental protocols used to detect protein interactions. This paper aims
at understanding the connection between true protein interactions and the
protein interaction datasets that have been obtained using the most popular
experimental techniques, i.e. mass spectronomy (MS) and yeast two-hybrid (Y2H).
We show that the most natural adjacency matrix of protein interaction networks
has a separable form, and this induces precise relations between moments of the
degree distribution and the number of short loops. These relations provide
powerful tools to test the reliability of datasets and hint at the underlying
biological mechanism with which proteins and complexes recruit each other.

Disordered Systems and Neural Networks