Trends in the development of miRNA bioinformatics tools

• Published in: Briefings in bioinformatics Vol. 20; no. 5; pp. 1836 - 1852
• Main Authors: Chen, Liang, Heikkinen, Liisa, Wang, Changliang, Yang, Yang, Sun, Huiyan, Wong, Garry
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 27.09.2019; Oxford Publishing Limited (England)
• Subjects: Algorithms; Bioinformatics; Computational Biology - methods; Data mining; Epigenetics; Gene expression; Machine Learning; MicroRNAs; MicroRNAs - chemistry; MicroRNAs - genetics; miRNA; Network analysis; Nucleic Acid Conformation; Predictions; Review; Ribonucleic acid; RNA; Target recognition; Trends; bibliometric; miRNA; text mining; ranking; bioinformatics tools
• ISSN: 1467-5463; 1477-4054
• DOI: 10.1093/bib/bby054

Abstract MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.