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 network's weight and connectivity properties.

An Evaluation Tool for Backbone Extraction Techniques in Weighted Complex Networks

“…Backbone extraction has a wide range of applications. One uses it for various types of networks, such as social [61][62][63][64][65][66][67][68][69] , biological 70 , brain [71][72][73][74] , gene [75][76][77][78][79] , metabolic [80][81][82][83][84] , food web 85,86 , environmental 87,88 , finance [89][90][91][92] , trade [93][94][95][96][97] , information [98][99][100][101] , political 102,103 , transportation [104][105][106][107][108] , and others [109][110]…”