Joint loop end modeling improves covariance model based non-coding RNA gene search

  • Authors:

  • Jennifer Smith

  • Affiliations:

  • Electrical and Computer Engineering Department, Boise State University, Boise, Idaho

  • Venue:
  • PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
  • Year:
  • 2010

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Abstract

The effect of more detailed modeling of the interface between stem and loop in non-coding RNA hairpin structures on efficacy of covariance-model-based non-coding RNA gene search is examined. Currently, the prior probabilities of the two stem nucleotides and two loop-end nucleotides at the interface are treated the same as any other stem and loop nucleotides respectively. Laboratory thermodynamic studies show that hairpin stability is dependent on the identities of these four nucleotides, but this is not taken into account in current covariance models. It is shown that separate estimation of emission priors for these nucleotides and joint treatment of substitution probabilities for the two loop-end nucleotides leads to improved noncoding RNA gene search.