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Reeder, Janina; Steffen, Peter; Giegerich, Robert: Effective ambiguity checking in biosequence analysis. In: BMC Bioinformatics. Jg.6 H. 1. 2005
Inhalt
Previous work
Formalization of ambiguity
Formal grammars
Context free grammars
Stochastic context free grammars
Syntactic versus semantic ambiguity
Semantic ambiguity in dynamic programming
SCFGs for RNA secondary structure analysis
Results and discussion
Sources of ambiguity, and how to avoid them
Three simple cases
Degree of ambiguity and consequences for testing
Testing for ambiguity
Algorithmic arsenal for ambiguity testing
Testing procedures
Brute force testing
Sampling structures from sample sequences
Structure counting for sample sequences
Just-in-time testing
Proving non-ambiguity
Semantic ambiguity in dynamic programming is unde-cidable
Theorem 1 Semantic ambiguity in dynamic programming is formally undecidable
Proof
Hand-made proof of non-ambiguity
Mechanical proof of non-ambiguity
Ambiguity reduction
Theorem 2 Let G* be derived from G according to the above rules. Then, G* is fl-ambiguous if and only if G is semantically ambiguous
Proof
Non-ambiguity proof
Applications
Table 1
Experience from a larger example
Conclusion
Methods
Authors' contributions
Appendix: Ambiguity in DP is undecidable
Theorem 1 Semantic ambiguity in dynamic programming is formally undecidable
Proof
Note
Acknowledgements
References