Exact Learning of RNA Energy Parameters From Structure

@article{Chitsaz2015ExactLO,
  title={Exact Learning of RNA Energy Parameters From Structure},
  author={H. Chitsaz and Mohammad Aminisharifabad},
  journal={Journal of computational biology : a journal of computational molecular cell biology},
  year={2015},
  volume={22 6},
  pages={
          463-73
        }
}
  • H. Chitsaz, Mohammad Aminisharifabad
  • Published 2015
  • Mathematics, Medicine, Biology, Computer Science
  • Journal of computational biology : a journal of computational molecular cell biology
We consider the problem of exact learning of parameters of a linear RNA energy model from secondary structure data. A necessary and sufficient condition for learnability of parameters is derived, which is based on computing the convex hull of union of translated Newton polytopes of input sequences. The set of learned energy parameters is characterized as the convex cone generated by the normal vectors to those facets of the resulting polytope that are incident to the origin. In practice, the… Expand
10 Citations
Statistical Method to Model the Quality Inconsistencies of the Welding Process
  • PDF

References

SHOWING 1-10 OF 49 REFERENCES
The RNA Newton polytope and learnability of energy parameters
  • 3
  • PDF
Computational approaches for RNA energy parameter estimation.
  • 99
  • PDF
Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.
  • 3,585
  • PDF
A dynamic programming algorithm for RNA structure prediction including pseudoknots.
  • 760
  • PDF
Rich Parameterization Improves RNA Structure Prediction
  • 46
  • PDF
Partition function and base pairing probabilities of RNA heterodimers
  • 248
  • PDF
Target prediction and a statistical sampling algorithm for RNA–RNA interaction
  • 49
  • PDF
biRNA: Fast RNA-RNA Binding Sites Prediction
  • 36
  • PDF
...
1
2
3
4
5
...