.png){kind=icon}
返回
Viral Genome Deep Classifier
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2923687.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The task of virus classification into subtypes is an important concern in many categorization studies, e.g., in virology or epidemiology. Therefore, the problem of virus subtyping has been a subject of considerable interest in the last decade. Although there exist several virus subtyping tools, they are often dedicated to a specific family of viruses. Even specialized methods, however, often fail to correctly subtype viruses, such as HIV or infiuenza. To address these shortcomings, we present a viral genome deep classifier (VGDC)-a tool for an automatic virus subtyping, which employs a deep convolutional neural network (CNN). The method is universal and can be applied for subtyping any virus, as confirmed by experiments on dengue, hepatitis B and C, HIV-1, and infiuenza A datasets. For all considered virus types, the obtained classification rates are very high with the corresponding values of the F1-score ranging from about 0.85 to 1.00 depending on the virus type and the considered number of subtypes. For HIV-1 and infiuenza A, the VGDC significantly outperforms the leading competitors, including CASTOR and COMET. The VGDC source code is freely available to facilitate easy usage and comparison with future approaches.
Keyword:
Genome
virus
subtyping
classification
convolutional neural network
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏分享收藏A deep learning framework for modeling structural features of RNA-binding protein targetsNUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏Detection and measurement of the Wing-Ford band in the near-infrared spectra of elliptical galaxies
OAAI
OAAI分享收藏分享收藏
查看更多内容