RNA-RNA interaction prediction based on multiple sequence alignments
Andrew X. Li, Manja Marz, Jing Qin, Christian M.Reidys

TL;DR
The paper introduces ripalign, an algorithm that predicts RNA-RNA interactions by integrating thermodynamic stability with evolutionary information from multiple sequence alignments, providing detailed probabilistic and structural outputs.
Contribution
It presents ripalign, a novel method that incorporates multiple sequence alignments into RNA-RNA interaction prediction, enhancing accuracy by considering evolutionary covariation.
Findings
ripalign computes partition functions and base-pairing probabilities effectively.
It requires minimal additional memory compared to single-sequence algorithms.
The method allows incorporation of structural constraints.
Abstract
Many computerized methods for RNA-RNA interaction structure prediction have been developed. Recently, time and space dynamic programming algorithms have become available that compute the partition function of RNA-RNA interaction complexes. However, few of these methods incorporate the knowledge concerning related sequences, thus relevant evolutionary information is often neglected from the structure determination. Therefore, it is of considerable practical interest to introduce a method taking into consideration both thermodynamic stability and sequence covariation. We present the \emph{a priori} folding algorithm \texttt{ripalign}, whose input consists of two (given) multiple sequence alignments (MSA). \texttt{ripalign} outputs (1) the partition function, (2) base-pairing probabilities, (3) hybrid probabilities and (4) a set of Boltzmann-sampled suboptimal structures…
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Taxonomy
TopicsRNA and protein synthesis mechanisms · RNA Research and Splicing · RNA modifications and cancer
