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Preprints, Working Papers, ... Year : 2016

Improved RNA pseudoknots prediction and classification using a new topological invariant

Abstract

We propose a new topological characterization of RNA secondary structures with pseudoknots based on two topological invariants. Starting from the classic arc-representation of RNA secondary structures, we consider a model that couples both I) the topological genus of the graph and II) the number of crossing arcs of the corresponding primitive graph. We add a term proportional to these topological invariants to the standard free energy of the RNA molecule, thus obtaining a novel free energy parametrization which takes into account the abundance of topologies of RNA pseudoknots observed in RNA databases.
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Dates and versions

cea-01327864 , version 1 (07-06-2016)

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Graziano Vernizzi, Henri Orland, A. Zee. Improved RNA pseudoknots prediction and classification using a new topological invariant. 2016. ⟨cea-01327864⟩
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