{"title":"gcCov：全球冠状病毒研究的关联开放数据。","authors":"Wenyu Shi, Guomei Fan, Zhihong Shen, Chuan Hu, Juncai Ma, Yuanchun Zhou, Zhen Meng, Songnian Hu, Yuhai Bi, Liang Wang, Haiying Yu, Siru Lin, Xiuqiang Sun, Xinjiao Zhang, Dongmei Liu, Qinlan Sun, Linhuan Wu","doi":"10.1002/mlf2.12008","DOIUrl":null,"url":null,"abstract":"<p><p>We present a method of mapping data from publicly available genomics and publication resources to the Resource Description Framework (RDF) and implement a server to publish linked open data (LOD). As one of the largest and most comprehensive semantic databases about coronaviruses, the resulted gcCov database demonstrates the capability of using data in the LOD framework to promote correlations between genotypes and phenotypes. These correlations will be helpful for future research on fundamental viral mechanisms and drug and vaccine designs. These LOD with 62,168,127 semantic triplets and their visualizations are freely accessible through gcCov at https://nmdc.cn/gccov/.</p>","PeriodicalId":94145,"journal":{"name":"mLife","volume":"1 1","pages":"92-95"},"PeriodicalIF":4.5000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9088579/pdf/","citationCount":"0","resultStr":"{\"title\":\"gcCov: Linked open data for global coronavirus studies.\",\"authors\":\"Wenyu Shi, Guomei Fan, Zhihong Shen, Chuan Hu, Juncai Ma, Yuanchun Zhou, Zhen Meng, Songnian Hu, Yuhai Bi, Liang Wang, Haiying Yu, Siru Lin, Xiuqiang Sun, Xinjiao Zhang, Dongmei Liu, Qinlan Sun, Linhuan Wu\",\"doi\":\"10.1002/mlf2.12008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We present a method of mapping data from publicly available genomics and publication resources to the Resource Description Framework (RDF) and implement a server to publish linked open data (LOD). As one of the largest and most comprehensive semantic databases about coronaviruses, the resulted gcCov database demonstrates the capability of using data in the LOD framework to promote correlations between genotypes and phenotypes. These correlations will be helpful for future research on fundamental viral mechanisms and drug and vaccine designs. These LOD with 62,168,127 semantic triplets and their visualizations are freely accessible through gcCov at https://nmdc.cn/gccov/.</p>\",\"PeriodicalId\":94145,\"journal\":{\"name\":\"mLife\",\"volume\":\"1 1\",\"pages\":\"92-95\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9088579/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"mLife\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/mlf2.12008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/3/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"mLife","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/mlf2.12008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/3/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
gcCov: Linked open data for global coronavirus studies.
We present a method of mapping data from publicly available genomics and publication resources to the Resource Description Framework (RDF) and implement a server to publish linked open data (LOD). As one of the largest and most comprehensive semantic databases about coronaviruses, the resulted gcCov database demonstrates the capability of using data in the LOD framework to promote correlations between genotypes and phenotypes. These correlations will be helpful for future research on fundamental viral mechanisms and drug and vaccine designs. These LOD with 62,168,127 semantic triplets and their visualizations are freely accessible through gcCov at https://nmdc.cn/gccov/.
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