The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data

@article{Parisien2008TheMA,
  title={The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data},
  author={Marc Parisien and François Major},
  journal={Nature},
  year={2008},
  volume={452},
  pages={51-55}
}
The classical RNA secondary structure model considers A·U and G·C Watson–Crick as well as G·U wobble base pairs. Here we substitute it for a new one, in which sets of nucleotide cyclic motifs define RNA structures. This model allows us to unify all base pairing energetic contributions in an effective scoring function to tackle the problem of RNA folding. We show how pipelining two computer algorithms based on nucleotide cyclic motifs, MC-Fold and MC-Sym, reproduces a series of experimentally… 
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