Figure 5.

The use case of CROssBAR COVID-19 knowledge graphs (https://crossbar.kansil.org/covid_main.php): (A) the large-scale KG (1289 nodes and 6743 edges) and (B) the simplified KG (435 nodes and 1061 edges). Both of these graphs reveal the most overrepresented biological processes during a SARS-CoV-2 infection (i.e. cell cycle, viral mRNA translation, endocytosis, interleukin signalling, etc.), as well as, the potential treatment options with COVID-19 related pre-clinical/clinical results (e.g. Remdesivir, Favipiravir, Dexamethasone, etc.) and our novel in silico predictions (for both virus and host proteins) considering long-term drug discovery or short-term drug repositioning applications (e.g. tocilizumab, cyclosporine, becatecarin, tenecteplase, simvastatin, etc.). It also displays rare and complex diseases and phenotypic implications with similar host protein associations (e.g. arthritis, diabetes, respiratory distress, fever, etc.).