Wen Zhongqi, Yan Cheng, Duan Guihua, Li Suning, Wu Fang-Xiang, Wang Jianxin
Hunan Provincial Key Lab of Bioinformatics, School of Computer Science and Engineering at Central South University, Hunan, China.
School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
Brief Bioinform. 2021 May 20;22(3). doi: 10.1093/bib/bbaa157.
Various microbes have proved to be closely related to the pathogenesis of human diseases. While many computational methods for predicting human microbe-disease associations (MDAs) have been developed, few systematic reviews on these methods have been reported. In this study, we provide a comprehensive overview of the existing methods. Firstly, we introduce the data used in existing MDA prediction methods. Secondly, we classify those methods into different categories by their nature and describe their algorithms and strategies in detail. Next, experimental evaluations are conducted on representative methods using different similarity data and calculation methods to compare their prediction performances. Based on the principles of computational methods and experimental results, we discuss the advantages and disadvantages of those methods and propose suggestions for the improvement of prediction performances. Considering the problems of the MDA prediction at present stage, we discuss future work from three perspectives including data, methods and formulations at the end.
各种微生物已被证明与人类疾病的发病机制密切相关。虽然已经开发了许多用于预测人类微生物-疾病关联（MDA）的计算方法，但关于这些方法的系统综述却鲜有报道。在本研究中，我们对现有方法进行了全面概述。首先，我们介绍了现有MDA预测方法中使用的数据。其次，我们根据其性质将这些方法分为不同类别，并详细描述它们的算法和策略。接下来，使用不同的相似性数据和计算方法对代表性方法进行实验评估，以比较它们的预测性能。基于计算方法的原理和实验结果，我们讨论了这些方法的优缺点，并提出了提高预测性能的建议。考虑到现阶段MDA预测存在的问题，最后我们从数据、方法和公式三个角度讨论了未来的工作。
