Virus classification for viral genomic fragments using PhaGCN2

• Published in: Briefings in bioinformatics Vol. 24; no. 1
• Main Authors: Jiang, Jing-Zhe, Yuan, Wen-Guang, Shang, Jiayu, Shi, Ying-Hui, Yang, Li-Ling, Liu, Min, Zhu, Peng, Jin, Tao, Sun, Yanni, Yuan, Li-Hong
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 19.01.2023; Oxford Publishing Limited (England)
• Subjects: Classification; Databases, Factual; Genome, Viral; Genomics; Sequences; Software; Source code; State-of-the-art reviews; Taxonomy; Viruses; Viruses - genetics; graph convolutional network; semi-supervised machine learning; virus classification; PhaGCN2; ICTV

Abstract 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 taxon...