Classifying RNA pseudoknotted structures

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Classifying RNA pseudoknotted structures

Computational prediction of the minimum free energy (mfe) secondary structure of an RNA molecule from its base sequence is valuable in understanding the structure and function of the molecule. Since the general problem of predicting pseudoknotted secondary structures is NP-hard, several algorithms have been proposed that find the mfe secondary structure from a restricted class of secondary stru...

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Counting RNA Pseudoknotted Structures

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 ...

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Predicting pseudoknotted structures across two RNA sequences

MOTIVATION Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accura...

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Counting RNA pseudoknotted structures ( extended abstract )

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 ...

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Counting RNA pseudoknotted structures ( extended abstract ) Cédric Saule

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 ...

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ژورنال

عنوان ژورنال: Theoretical Computer Science

سال: 2004

ISSN: 0304-3975

DOI: 10.1016/j.tcs.2004.03.042