A reliable and unbiased human protein network with the disparity filter
Abstract
The living cell operates thanks to an intricate network of protein interactions. Proteins activate, transport, degrade, stabilise and participate in the production of other proteins. As a result, a reliable and systematically generated protein wiring diagram is crucial for a deeper understanding of cellular functions. Unfortunately, current human protein networks are noisy and incomplete. Also, they suffer from both study and technical biases: heavily studied proteins (e.g. those of pharmaceutical interest) are known to be involved in more interactions than proteins described in only a few publications. Here, we use the experimental evidence supporting the interaction between proteins, in conjunction with the so-called disparity filter, to construct a reliable and unbiased proteome-scale human interactome. The application of a global filter, i.e. only considering interactions with multiple pieces of evidence, would result in an excessively pruned network. In contrast, the disparity filter preserves interactions supported by a statistically significant number of studies and does not overlook small-scale protein associations. The resulting disparity-filtered protein network covers 67% of the human proteome and retains most of the networks weight and connectivity properties.
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