Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

• Published in: Briefings in bioinformatics Vol. 23; no. 6
• Main Authors: Huang, Li, Zhang, Li, Chen, Xing
• Format: Journal Article
• Language: English
• Published: England 19.11.2022
• Subjects: Algorithms; Computational Biology - methods; Databases, Genetic; Genetic Predisposition to Disease; Humans; MicroRNAs - genetics; Neoplasms - genetics; PubMed; data fusion; databases; microRNA; microRNA-disease association prediction; complex diseases
• ISSN: 1467-5463; 1477-4054; 1477-4054
• DOI: 10.1093/bib/bbac397

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.