Here we present IRIS, a method for prediction of RNA-RNA interactions that is based on dynamic programming and extends current RNA secondary structure prediction approaches. Using this method we have found a number of interesting refinements to the structures of RNA-RNA complexes that have been studied previously and predicted novel targets for several known regulatory RNAs in E. coli. The computational time and memory usage of IRIS are O(n(3)m(3)) and O(n(2)m(2)), respectively, where n and m are the lengths of the input sequences. IRIS can be used for analysis of antisense regulatory systems in sequenced organisms and for the design of artificial riboregulators such as antisense drugs.
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