Sparse RNA folding revisited: space-efficient minimum free energy structure prediction
Algorithms for Molecular Biology(2016)
摘要
Background RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Results Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T ; both are bounded by n^2 , but are typically much smaller. The time complexity of RNA folding is reduced from O(n^3) to O(n^2+nZ) ; the space complexity, from O(n^2) to O(n + T + Z) . Our empirical results show more than 80
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关键词
Space efficient sparsification,Pseudoknot-free RNA folding,RNA secondary structure prediction
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