Comprehensive large-scale datasets for 26 viral families for fine-tuning BERT-infect models

These datasets were constructed in the paper "Hidden Challenges in Evaluating Spillover Risk of Zoonotic Viruses using Machine Learning Models" (doi: https://doi.org/10.1101/2024.04.25.591033). The details were also described in the git-hub (https://github.com/Junna-Kawasaki/BERT-infect_2024). The compressed files, such as ${virus}.tar.xz, contain fasta and genbank files.本数据集均构建自论文《利用机器学习模型评估人畜共患病毒溢出风险的隐藏挑战》（doi: https://doi.org/10.1101/2024.04.25.591033）。该数据集的详细信息同样在GitHub仓库（https://github.com/Junna-Kawasaki/BERT-infect_2024）中予以说明。 此类压缩文件（例如${virus}.tar.xz）内包含FASTA格式文件与GenBank格式文件。