Data Bias in protein-protein interactions data
I'm one of the STRING maintainers, so I hope I can clear things up a bit.

Gene co-occurrence: genomic context methods are very useful for bacterial genomes, but not so much for eukaryotes. However, they are actually the most unbiased data we have, since there's no human influence (beyond selecting species for sequencing).

Benchmarking: Interactions predicted from text-mining etc. are benchmarked against the KEGG database. However, this doesn't necessarily lead to biases, as this benchmarking is basically a calibration step.

Actual biases: For eukaryotes, most interaction data comes from the experimental, database and text-mining channel. All of these are biased in various ways: e.g. there are study biases (disease genes will get more attention) and technical biases (some proteins are hard to work with) 

As we don't know the actual set of protein-protein interactions, we can probably not test for biases in the data.