A survey on predicting microbe-disease associations: biological data and computational methods. Issue 3 (6th August 2020)

• Record Type: Journal Article
• Authors: Wen, Zhongqi; Yan, Cheng; Duan, Guihua; Li, Suning; Wu, Fang-Xiang; Wang, Jianxin
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 3(2021)
• Publication Date: 2020-08-06
• Subjects: microbe-disease prediction -- microbe/disease similarity -- similarity calculation method -- cross validation; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa157
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: 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.