Noncoding RNAs improve the predictive power of network medicine

These advances relied on maps of experimentally confirmed protein–protein interactions (PPI) and supported multiple foundational discoveries, like the tendency of proteins associated with the same disease to be co-l ocalized in the same neighborhood of the PPI network (4), the finding that diseases with similar phenotypes lie in similar regions of the interactome (4) and the discovery that the net. [...] We have also analyzed the crosslinked, Ligated, and Selected Hybrids), LIGRseq (LIGation of degree distribution of the PPI and the PPI & NCI networks, finding interacting RNA followed by high-t hroughput sequencing), and that while the inclusion of the NCI does not affect the scale- free MARIO (Mapping RNA interactome in vivo)], and targeted studies nature of the network (56), it does alter the co. [...] of this sub-n etwork measures the magnitude of the disease mod To generalize beyond RA, CD, and PE, we calculated the LCC, ule, and its statistical significance is obtained by deriving the LCC rLCC, and the significance of the disease module for all 861 diseases distribution based on the random selection of the disease- associated in the PPI and in the PPI & NCI. [...] Taken together, the relative LCC (rLCC), defined as the ratio between the size of we find that for 132 diseases the identification of a statistically LCC and the number of genes associated with the disease. [...] The histogram depicts LCC distribution for diseases in both PPI and PPI & NCI, the PPI (in purple) shows a distribution heavily shifted to the left, and the PPI & NCI (in turquoise) indicates a distribution that its values are shifting to the right, indicating that the average distribution of the LCCs in the combined network increases.