Generic placeholder image

Current Genomics


ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

In-Silico Algorithms for the Screening of Possible microRNA Binding Sites and Their Interactions

Author(s): Harsh Dweep, Carsten Sticht and Norbert Gretz

Volume 14 , Issue 2 , 2013

Page: [127 - 136] Pages: 10

DOI: 10.2174/1389202911314020005

Price: $65


MicroRNAs (miRNAs) comprise a recently discovered class of small, non-coding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the transcripts of their targets i.e. proteincoding genes, leading to down-regulation or repression of the target genes. However, target gene activation has also been described. miRNAs are involved in diverse regulatory pathways, including control of developmental timing, apoptosis, cell proliferation, cell differentiation, modulation of immune response to macrophages, and organ development and are associated with many diseases, such as cancer. Computational prediction of miRNA targets is much more challenging in animals than in plants, because animal miRNAs often perform imperfect base-pairing with their target sites, unlike plant miRNAs which almost always bind their targets with near perfect complementarity. In the past years, a large number of target prediction programs and databases on experimentally validated information have been developed for animal miRNAs to fulfil the need of experimental scientists conducting miRNA research. In this review we first succinctly describe the prediction criteria (rules or principles) adapted by prediction algorithms to generate possible miRNA binding site interactions and introduce most relevant algorithms, and databases. We then summarize their applications with the help of some previously published studies. We further provide experimentally validated functional binding sites outside 3’-UTR region of target mRNAs and the resources which offer such predictions. Finally, the issue of experimental validation of miRNA binding sites will be briefly discussed.

Keywords: microRNAs, miRWalk, Target prediction, Promoter, CDS, UTR, Prediction algorithm, Database

Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy