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|@@ -2,12 +2,10 @@|
|-In this article we presented a new and efficient way of|
|-exploring the mutational landscape of an RNA, benefiting from the|
|- conserved consensus secondary structures information,|
|-to identify and fix sequencing errors. We additionally introduce a new|
|- pseudo energy model, both taking into account the nearest-neighbour energy model|
|-and, to account for geometrical discrepancies, the isostericity of all base pairs.|
|+In this article we presented a new and efficient way of exploring the mutational landscape of an RNA under structural constraints,|
|+and apply our techniques to identify and fix sequencing errors. In adddition, we introduce a new|
|+scoring scheme combining the nearest-neighbour energy model to new isostericity matrices in order to account for geometrical|
|+discrepancies occurring during base pair replacements.|
|The algorithm runs in $\Theta(n\cdot(|\Omega|+m^2))$ time and $\Theta(n\cdot(|\Omega|+m))$ memory, where $n$ is the length of the RNA,|
|$m$ the number of mutations and $\Omega$ the size of the multiple sequence alignment.|