
In 2004, Condon and coauthors gave a hierarchical classification of exact RNA structure prediction algorithms according to the generality of structure classes that they handle. We complete this classification by adding two recent prediction algorithms. More importantly, we precisely quantify the hierarchy by giving closed or asymptotic formulas for the theoretical number of structures of given size n in all the classes but one. This allows us to assess the tradeoff between the expressiveness and the computational complexity of RNA structure prediction algorithms.
Models, Molecular, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Sequence Analysis, RNA, Computational Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 004, 510, Nucleic Acid Conformation, RNA, Computer Simulation, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Algorithms, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], Probability
Models, Molecular, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Sequence Analysis, RNA, Computational Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 004, 510, Nucleic Acid Conformation, RNA, Computer Simulation, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Algorithms, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], Probability
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