Abstract
BackgroundExperimental identification of microRNA (miRNA) targets is a difficult and time consuming process. As a consequence several computational prediction methods have been devised in order to predict targets for follow up experimental validation. Current computational target prediction methods use only the miRNA sequence as input. With an increasing number of experimentally validated targets becoming available, utilising this additional information in the search for further targets may help to improve the specificity of computational methods for target site prediction.ResultsWe introduce a generic target prediction method, the Stacking Binding Matrix (SBM) that uses both information about the miRNA as well as experimentally validated target sequences in the search for candidate target sequences. We demonstrate the utility of our method by applying it to both animal and plant data sets and compare it with miRanda, a commonly used target prediction method.ConclusionWe show that SBM can be applied to target prediction in both plants and animals and performs well in terms of sensitivity and specificity. Open source code implementing the SBM method, together with documentation and examples are freely available for download from the address in the Availability and Requirements section.
Highlights
Experimental identification of microRNA targets is a difficult and time consuming process
Several computational methods have been developed for miRNA target prediction – see e.g. [10,11,12,13]
To demonstrate the utility of the Stacking Binding Matrix (SBM) method, we present an application to the problem of miRNA target detection for nematode worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), mouse (Mus musculus), human (Homo sapiens) and thale cress (Arabidopsis thaliana)
Summary
Experimental identification of microRNA (miRNA) targets is a difficult and time consuming process. MicroRNAs (miRNAs) are small non-coding RNAs of around 21 nt in length, which are currently receiving a great deal of attention [1,2] They are derived from a precursor RNA hairpin structure by RNAse III-like enzymes [3], and are incorporated into the RNA induced silencing complex (RISC). Via this complex, the microRNA guides either the cleavage or translational repression of messenger RNAs (mRNAs) by binding to a region of the mRNA known as the target site [4]. These methods usually rely on finding target sequences based on a single miRNA input, and employ nucleotide complementarity and minimum free energy (MFE) calculations to identify candidate miRNA/target duplexes These methods have been successfully used in target prediction e.g. These methods have been successfully used in target prediction e.g. [14], their specificity can be limited, i.e. they may produce many false positives [15]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
