VirNucPro:一种用于识别病毒短序的标识符,使用六翻译和大型语言模型识别病毒短序
1The College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North Third Ring East Road, Chaoyang District, Beijing 100029, China.
Briefings in bioinformatics
|May 19, 2025
概括
一个新的模型,VirNucPro,通过结合核酸和氨基酸数据,准确地识别短病毒序列. 这一进步改善了从测序数据中发现病毒的发现,即使是碎片化的序列.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 病毒学 病毒学
背景情况:
- 病毒广泛传播,但人们对其了解甚少.
- 高通量测序产生了大量的数据,但病毒序列只是很小的一小部分,很难识别.
- 短且碎片化的病毒序列由于有限的特征,挑战了现有的识别模型.
研究的目的:
- 开发一种新型模型,VirNucPro,用于准确识别短病毒序列.
- 从复杂的生物样本中提高病毒序列的分辨率.
- 改进高通量测序数据中病毒遗传物质的检测.
主要方法:
- 开发了VirNucPro,这是一个整合核酸和氨基酸序列信息的模型.
- 采用六翻译策略和大型语言模型来增强功能提取.
- 进行了废弃实验,以评估不同序列特征的贡献.
主要成果:
- 在识别短病毒序列方面,VirNucPro实现了高精度.
- 氨基酸序列信息显著改善了分类性能.
- 该模型在短序 (300和500 bp) 上表现优于现有的方法,如GCNFrame,DeepVirFinder,DETIRE和Virtifier.
- 在真实世界数据集上表现出卓越的性能,并确定了细菌DNA中的prophage区域.
结论:
- VirNucPro提供了一个强大的新工具,用于简短的病毒序列识别.
- 氨基酸特征的整合对于准确的病毒检测至关重要.
- 该模型在病毒学和微生物基因组学中具有广泛的应用,包括prophage检测.
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