A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

@article{Rivas2012ARO,
  title={A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.},
  author={Elena Rivas and Raymond W. Lang and Sean R. Eddy},
  journal={RNA},
  year={2012},
  volume={18 2},
  pages={
          193-212
        }
}
The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been… 

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