Application of Machine Learning in Microbiology

Conclusion Microorganisms are involved in many life activities, and affect their surrounding environment and other organisms. Microorganisms play important roles in human heath, crop growth, livestock farming, environmental management, industrial chemical production and food production. In the 19th century, people first observed microbes using microscopes and began to study them. However, the development of high-throughput sequencing technology has led to generation of large amounts of microbial related data. As a result, machine-learning methods are now being applied to microbiological research. Here, we discuss the current application of ML in the microbiome. The results revealed that ML is widely used in microbiological research, and that it has focused on classification problems and analysis of interaction problems. However, many problems remain unresolved and will require the cooperation of researchers from different fields, such as biology, informatics and medicine, to jointly promote the development and progress of microbiological research. On the other hand, the recent developed link prediction (Liu et al., 2016; Zeng et al., 2017b) and computational intelligence methods (Cabarle et al., 2017; Song et al., 2018), can be promising in discovering the relationship between diseases and microbes. Author Contributions KQ drafted the manuscript. FG and XL conducted research. YL modified the manuscript. QZ conceived the idea. Funding The work was supported by the Nationa...
Source: Frontiers in Microbiology - Category: Microbiology Source Type: research