A scoring matrix approach to detecting miRNA target sites

Simon Moxon , Vincent Moulton and Jan T Kim

School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK

author email corresponding author email

Algorithms for Molecular Biology 2008, 3:3doi:10.1186/1748-7188-3-3


Published:	31 March 2008

Abstract

Background

Experimental 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.

Results

We 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.

Conclusion

We 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.