Code selection by inversion of order-sorted derivors
Proceedings of the Second European Symposium on Programming
Introduction to algorithms
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Estimating the Probability of Approximate Matches
CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
AMAST '02 Proceedings of the 9th International Conference on Algebraic Methodology and Software Technology
Prediction of RNA secondary structure including kissing hairpin motifs
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
Semantics and Ambiguity of Stochastic RNA Family Models
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Ambiguity in dynamic programming arises from two independent sources, the non-uniqueness of optimal solutions and the particular recursion scheme by which the search space is evaluated. Ambiguity, unless explicitly considered, leads to unnecessarily complicated, inflexible, and sometimes even incorrect dynamic programming algorithms. Building upon the recently developed algebraic approach to dynamic programming, we formalize the notions of ambiguity and canonicity. We argue that the use of canonical yield grammars leads to transparent and versatile dynamic programming algorithms. They provide a master copy of recurrences, that can solve all DP problems in a well-defined domain. We demonstrate the advantages of such a systematic approach using problems from the areas of RNA folding and pairwise sequence comparison.