Qu Kaiyang, Guo Fei, Liu Xiangrong, Lin Yuan, Zou Quan
College of Intelligence and Computing, Tianjin University, Tianjin, China.
School of Information Science and Technology, Xiamen University, Xiamen, China.
Front Microbiol. 2019 Apr 18;10:827. doi: 10.3389/fmicb.2019.00827. eCollection 2019.
Microorganisms are ubiquitous and closely related to people's daily lives. Since they were first discovered in the 19th century, researchers have shown great interest in microorganisms. People studied microorganisms through cultivation, but this method is expensive and time consuming. However, the cultivation method cannot keep a pace with the development of high-throughput sequencing technology. To deal with this problem, machine learning (ML) methods have been widely applied to the field of microbiology. Literature reviews have shown that ML can be used in many aspects of microbiology research, especially classification problems, and for exploring the interaction between microorganisms and the surrounding environment. In this study, we summarize the application of ML in microbiology.
微生物无处不在，与人们的日常生活密切相关。自19世纪首次被发现以来，研究人员对微生物表现出了极大的兴趣。人们通过培养来研究微生物，但这种方法既昂贵又耗时。然而，培养方法无法跟上高通量测序技术的发展步伐。为了解决这个问题，机器学习（ML）方法已被广泛应用于微生物学领域。文献综述表明，ML可用于微生物学研究的许多方面，特别是分类问题，以及探索微生物与周围环境之间的相互作用。在本研究中，我们总结了ML在微生物学中的应用。
