Stochastic Context-Free Grammars (SCFG) has been shown to be effective in modelling RNA secondary structure for searches. Our previous work (Cai et al., 2003) in Stochastic Parallel Communicating Grammar Systems (SPCGS) has extended SCFG to model RNA pseudoknots. However, the alignment algorithm requires O(n 4 ) memory for a sequence of length n. In this paper, we develop a memory efficient algorithm for sequence-structure alignments including pseudoknots. This new algorithm reduces the memory

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... pace requirement from O(n 4 ) to O(n 2 ) without increasing the computation time. Our experiments have shown that this novel approach can achieve excellent performance on searching for RNA pseudoknots. Reference to this paper should be made as follows: Song, Y., Liu, C., Malmberg, R.L., He, C. and Cai, L. (2006) 'Memory efficient alignment between RNA sequences and stochastic grammar models of pseudoknots', Int.