文献类型： 外文期刊
作者： Jiang, Jing-Zhe 1 ; Yuan, Wen-Guang 5 ; Shang, Jiayu 6 ; Shi, Ying-Hui 5 ; Yang, Li-Ling 1 ; Liu, Min 7 ; Zhu, Peng 7 ; Jin, Tao 1 ; Sun, Yanni 2 ; Yuan, Li-Hong 3 ;
作者机构： 1.Chinese Acad Fishery Sci, South China Sea Fisheries Res Inst, Key Lab South China Sea Fishery Resources Exploita, Minist Agr & Rural Affairs, Guangzhou 510300, Peoples R China
2.City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China
3.Guangdong Pharmaceut Univ, Sch Biosci & Biopharmaceut, Guangdong Prov Key Lab Biotechnol Drug Candidates, Guangzhou 510006, Peoples R China
4.Chinese Acad Fishery Sci, South China Sea Fisheries Res Inst, Guangzhou, Peoples R China
5.Guangdong Pharmaceut Univ, Guangzhou, Peoples R China
6.City Univ Hong Kong, Hong Kong, Peoples R China
7.Shanghai Ocean Univ, Shanghai, Peoples R China
8.Guangdong Pharmaceut Univ, Sch Biosci & Biopharmaceut, Guangzhou, Peoples R China
关键词： graph convolutional network; semi-supervised machine learning; virus classification; ICTV; PhaGCN2
期刊名称：BRIEFINGS IN BIOINFORMATICS （ 2021影响因子：13.994； 五年影响因子：12.784 ）
ISSN： 1467-5463
收录情况： SCI
摘要： Viruses are the most ubiquitous and diverse entities in the biome. Due to the rapid growth of newly identified viruses, there is an urgent need for accurate and comprehensive virus classification, particularly for novel viruses. Here, we present PhaGCN2, which can rapidly classify the taxonomy of viral sequences at the family level and supports the visualization of the associations of all families. We evaluate the performance of PhaGCN2 and compare it with the state-of-the-art virus classification tools, such as vConTACT2, CAT and VPF-Class, using the widely accepted metrics. The results show that PhaGCN2 largely improves the precision and recall of virus classification, increases the number of classifiable virus sequences in the Global Ocean Virome dataset (v2.0) by four times and classifies more than 90% of the Gut Phage Database. PhaGCN2 makes it possible to conduct high-throughput and automatic expansion of the database of the International Committee on Taxonomy of Viruses. The source code is freely available at .
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