For this we used Genes2Networks, which integrates the data contained in multiple interaction network datasets, enables the user to determine the path length (degree of interaction), and incorporates possible interacting proteins which are not part of the user's original input list.
The methodological aim of the present study was to enable an integrated analysis of multiple genetic interaction datasets using a common scoring framework.
Several studies have previously analyzed specific interaction datasets in multiple species and identified trends in these datasets that differentiated conserved and non conserved interactions.
This included information from protein-protein interaction screens obtained from multiple databases including Fly General Repository for Interaction Datasets (Fly GRID), Human Protein Reference Database (HPRD), PubMed Gene, and Genecards.
We used the "Y2H-union", "Combined-AP/MS" and "LC-multiple" datasets to represent typical protein interaction datasets obtained from Y2 H assays, the AP/MS method and literature curation, respectively.
1) Y2H-union: the union of three high-throughput Y2 H datasets: Uetz-screen [ 57], Ito-core [ 58] and CCSBYI1 [ 32]. 2) Combined-AP/MS: an integrated dataset [ 59] of two high-throughput AP/MS datasets [ 60, 61]. 3) LC-multiple: a protein interaction dataset based on the literature.
Specifically, significant results are observed for protein interaction datasets that include "Combined-AP/MS", "LC-multiple", "Updated-HC", "DIP-CORE" and "DIP-FULL".
The compact form is more suitable for larger datasets, where, for example, one protein would be referred to by multiple interaction elements.
The PBA material has multiple interaction mechanisms.
