Research progress on bioinformatics techniques for virus identification based on metagenomics
10.3760/cma.j.cn112150-20230919-00204
- VernacularTitle:基于宏基因组的病毒识别生物信息学技术研究进展
- Author:
Huakai HU
1
;
Xiong LIU
;
Jinpeng GUO
;
Yong CHEN
;
Changjun WANG
Author Information
1. 中国医科大学公共卫生学院，沈阳 110122
- Keywords:
Metagenomics;
Viruses;
Computational biology;
Machine learning
- From:
Chinese Journal of Preventive Medicine
2024;58(4):516-525
- CountryChina
- Language:Chinese
-
Abstract:
In recent years, global outbreaks of infectious diseases, such as COVID-19, have triggered great concern about emerging infectious diseases. With the rapid development of next-generation sequencing technology and bioinformatic tools for viral metagenomics, there is now a widespread capability to detect and identify various known and unknown pathogenic microorganisms within both environmental and biological contexts. Furthermore, the continuous evolution of machine learning methods has led to the development and application of multiple rapid and highly accurate approaches for virus identification. Concurrently, owing to the continual progress in machine learning methods, several rapid and accurate virus identification techniques have been widely developed and applied. Therefore, this review aims to systematically summarize the key methodologies, frameworks, and the scope of applicability within the field of viral metagenomics, with a specific focus on virus identification and prediction. It could facilitate a deeper understanding of viral characteristics, identify potential novel pathogens, and provide technical support for the early prevention and control of infectious diseases.
