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gcCov:Linked open data for global coronavirus studies
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作者 Wenyu Shi Guomei Fan +14 位作者 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 《mLife》 2022年第1期92-95,共4页
Impact Statement 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 ... Impact Statement 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. 展开更多
关键词 SERVER DATABASE DATABASES
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