A Review of Computational Tools in microRNA Discovery

Since microRNAs (miRNAs) were discovered, their impact on regulating various biological activities has been a surprising and exciting field. Knowing the entire repertoire of these small molecules is the first step to gain a better understanding of their function. High throughput discovery tools such...

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Bibliographic Details
Published in:Frontiers in genetics 2013, Vol.4, p.81-81
Main Authors: Gomes, Clarissa P C, Cho, Ji-Hoon, Hood, Leroy, Franco, Octávio L, Pereira, Rinaldo W, Wang, Kai
Format: Article
Language:English
Subjects:
Genetics
isomiRs
machine learning
miRNA conservation
RNA secondary structure
Sequence Homology
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Summary:Since microRNAs (miRNAs) were discovered, their impact on regulating various biological activities has been a surprising and exciting field. Knowing the entire repertoire of these small molecules is the first step to gain a better understanding of their function. High throughput discovery tools such as next-generation sequencing significantly increased the number of known miRNAs in different organisms in recent years. However, the process of being able to accurately identify miRNAs is still a complex and difficult task, requiring the integration of experimental approaches with computational methods. A number of prediction algorithms based on characteristics of miRNA molecules have been developed to identify new miRNA species. Different approaches have certain strengths and weaknesses and in this review, we aim to summarize several commonly used tools in metazoan miRNA discovery.
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2013.00081