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What do you mean by validating? PPI's are normally based on experimental data already.
To know if my network is not something random, but a network with "biological validation".
Or is it not necessary?
The PPIs are already based on high-throughput screens. As with every screen, it provided candidates to further investigate. Depending on your biological question, the data now need to be further analyzed by experiments in more detail. But I am not sure if I get the question correctly.
Like this paper: 1. This is required? 2. Is there another way to do it?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3641020/
In order to validate the robustness of the backbone network and the NOS3 as central protein, we constructed test networks only using a part of 69 genes as initial seeds. The initial seed genes were determined by omitting from 1 to 7 (10% of 69) genes. If the number of the omitted genes is 3, there are 314364 (69 × 68 × 67) combinations. Therefore, the omitted genes were selected randomly if the number of omitted genes is more than 3. However, considering the importance of NOS3 in our conclusion, NOS3 was omitted always. Then the exact method of omitting genes is as below. If the number of omitted gene is 1, then there are 69 combinations because every gene of 69 genes was omitted once. If the number of omitted gene is 2, then there are 68 combinations (NOS3 and other 68 genes). If the number of omitted genes is more than 3, the omitted genes are NOS3 and other genes selected randomly and regardless of number of omitted genes, randomly selecting is 30 times. Finally, 287 test networks (69 + 68 + 5*30) ware constructed (Additional file 1), and the BC values of nodes in these networks ware calculated by Pajek software. Then the nodes with top 27 BC value were determined in these test networks. We tested the robustness of the backbone network and the NOS3 as central protein by calculating frequency of NOS3 as a node with the largest BC value and the accuracy of the backbone nodes in the test networks. The accuracy of backbone was estimated as the fraction of the nodes with top 27 BC in the test networks which agree with the nodes in the backbone network described in step five.