{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:09:52Z","timestamp":1760234992141,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T00:00:00Z","timestamp":1624924800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2019R1A2C2002577"],"award-info":[{"award-number":["NRF-2019R1A2C2002577"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Science Foundation in the United States","award":["NSF Rapid 2028717"],"award-info":[{"award-number":["NSF Rapid 2028717"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a collection of published scientific articles related to COVID-19. We combined both chemo genomic entities in AG with entities extracted from CORD-19 to expand knowledge in the COVID-19 domain. Before populating KG with those entities, we perform entity disambiguation on CORD-19 collections using Wikidata. Our newly built KG contains at least 21,700 genes, 2500 diseases, 94,000 phenotypes, and other biological entities (e.g., compound, species, and cell lines). We define 27 relationship types and use them to label each edge in our KG. This research presents two cases to evaluate the KG\u2019s usability: analyzing a subgraph (ego-centered network) from the angiotensin-converting enzyme (ACE) and revealing paths between biological entities (hydroxychloroquine and IL-6 receptor; chloroquine and STAT1). The ego-centered network captured information related to COVID-19. We also found significant COVID-19-related information in top-ranked paths with a depth of three based on our path evaluation.<\/jats:p>","DOI":"10.3390\/genes12070998","type":"journal-article","created":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T10:52:46Z","timestamp":1624963966000},"page":"998","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Toward a Coronavirus Knowledge Graph"],"prefix":"10.3390","volume":"12","author":[{"given":"Peng","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2549-4580","authenticated-orcid":false,"given":"Yi","family":"Bu","sequence":"additional","affiliation":[{"name":"Department of Information Management, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Beijing Knowledge Atlas Technology Co., Ltd., Beijing 100043, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaowen","family":"Shi","sequence":"additional","affiliation":[{"name":"Beijing Knowledge Atlas Technology Co., Ltd., Beijing 100043, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Lun","sequence":"additional","affiliation":[{"name":"Beijing Knowledge Atlas Technology Co., Ltd., Beijing 100043, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3188-6652","authenticated-orcid":false,"given":"Chongyan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information, University of Texas at Austin, Austin, TX 78701, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arida Ferti","family":"Syafiandini","sequence":"additional","affiliation":[{"name":"Department of Library and Information Science, Yonsei University, Seoul 03722, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information, University of Texas at Austin, Austin, TX 78701, USA"},{"name":"Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Library and Information Science, Yonsei University, Seoul 03722, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,29]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (WHO) (2020, August 05). 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