title: A Review of Computational Tools in microRNA Discovery.
abstract: 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.
authors.affiliation: Institute for Systems Biology Seattle, WA, USA ; Pós-Graduaçao em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília Brasília, Brazil ; Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília Brasília, Brazil.
authors.forename: Clarissa P C
authors.initials: CP
authors.lastname: Gomes
authors.forename: Ji-Hoon
authors.initials: JH
authors.lastname: Cho
authors.forename: Leroy
authors.initials: L
authors.lastname: Hood
authors.forename: Octávio L
authors.initials: OL
authors.lastname: Franco
authors.forename: Rinaldo W
authors.initials: RW
authors.lastname: Pereira
authors.forename: Kai
authors.initials: K
authors.lastname: Wang
keywords: RNA secondary structure; isomer; machine learning; miRNA conservation; sequence homology