Refining microRNA target predictions: Sorting the wheat from the chaff

•The principles underlying most commonly used microRNA target prediction algorithms.•An evaluation of the experimental data that supports each computational approach.•An evaluation of microRNA target databases, their strengths and weaknesses. microRNAs are short RNAs that reduce gene expression by b...

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Bibliographic Details
Published in:Biochemical and biophysical research communications 2014-03, Vol.445 (4), p.780-784
Main Authors: Ritchie, William, Rasko, John E.J.
Format: Article
Language:English
Subjects:
Algorithms
Animals
Bioinformatics
Gene Expression Regulation
gene regulation
Genomics - methods
Humans
microRNA target prediction
MicroRNAs - chemistry
MicroRNAs - genetics
MicroRNAs - metabolism
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Summary:•The principles underlying most commonly used microRNA target prediction algorithms.•An evaluation of the experimental data that supports each computational approach.•An evaluation of microRNA target databases, their strengths and weaknesses. microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.
ISSN:0006-291X
1090-2104
DOI:10.1016/j.bbrc.2014.01.181