Structural analysis of aligned RNAs

The knowledge about classes of non-coding RNAs (ncRNAs) is growing very fast and it is mainly the structure which is the common characteristic property shared by members of the same class. For correct characterization of such classes it is therefore of great importance to analyse the structural features in great detail. In this manuscript I present RNAlishapes which combines various secondary structure analysis methods, such as suboptimal folding and shape abstraction, with a comparative approach known as RNA alignment folding. RNAlishapes makes use of an extended thermodynamic model and covariance scoring, which allows to reward covariation of paired bases. Applying the algorithm to a set of bacterial trp-operon leaders using shape abstraction it was able to identify the two alternating conformations of this attenuator. Besides providing in-depth analysis methods for aligned RNAs, the tool also shows a fairly well prediction accuracy. Therefore, RNAlishapes provides the community with a powerful tool for structural analysis of classes of RNAs and is also a reasonable method for consensus structure prediction based on sequence alignments. RNAlishapes is available for online use and download at

Challenges in the Compilation of a Domain Specific Language for Dynamic Programming

Giegerich R, Steffen P. Challenges in the Compilation of a Domain Specific Language for Dynamic Programming. In: Proceedings of te 2006 ACM Symposium on Applied Computing. 2006

Challenges in the Compilation of a Domain Specific Language for Dynamic Programming ABSTRACT

Many combinatorial optimization problems in biosequence analysis are solved via dynamic programming. To increase programming productivity and program reliability, a domain specific language embedded in Haskell has been suggested. We point out several shortcomings of this approach, and report on some challenges in the (ongoing) project of migrating this domain specific language from its host language to a directly compiled implementation. Most of these challenges are domain specific optimizations, which not only improve significant constant factors of runtime and space requirements, but also affect asymptotic efficiency. We report on our solutions to some of these problems, and point out others that are still open