Скачать или смотреть Literature-derived host-coronavirus gene-gene interaction network of SARS-CoV-2

By Junguk Hur, Anthony Huffman, Mert Basmaci, Edison Ong, Arzucan Ozgur, and Yongqun He

Human coronaviruses have given rise to a series of major crises in global public health. The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2, has caused over 24.9 million confirmed cases with 838 thousand deaths worldwide and 5.0 million confirmed cases with 183 thousand deaths in the USA alone. Numerous research on COVID-19 is ongoing and their novel findings are published daily. To develop efficient mechanism-based therapeutics against COVID-19, it is critical to systematically study the interactions between hosts and coronaviruses. In this study, we used our in-house centrality- and network-based literature mining analysis platform, SciMiner, to perform a preliminary gene-interaction analysis of COVID-19. The abstracts of 32,363 COVID-19-related articles, compiled in LitCovid, a curated literature hub containing up-to-date scientific information about the 2019 novel Coronavirus. SciMiner identified 103 host genes and 19 coronavirus genes, represented in terms of Ontology of Genes and Genomes, and 226 unique interactions among them, detected at the sentence level. These interactions were clearly separated into two clusters, one related to viral invasion and another one associated with host-immune responses. This comprehensive literature-derived COVID-19 gene interaction network may facilitate the generation of novel hypotheses about pathogenic mechanisms and the identification of potential therapeutic targets.

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