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Rna Search With Decision Trees And Partial Covariance Models, Jennifer A. Smith
Rna Search With Decision Trees And Partial Covariance Models, Jennifer A. Smith
Jennifer A. Smith
The use of partial covariance models to search for RNA family members in genomic sequence databases is explored. The partial models are formed from contiguous subranges of the overall RNA family multiple alignment columns. A binary decision-tree framework is presented for choosing the order to apply the partial models and the score thresholds on which to make the decisions. The decision trees are chosen to minimize computation time subject to the constraint that all of the training sequences are passed to the full covariance model for final evaluation. Computational intelligence methods are suggested to select the decision tree since the …
Improved Covariance Model Parameter Estimation Using Rna Thermodynamic Properties, Jennifer A. Smith, Kay C. Wiese
Improved Covariance Model Parameter Estimation Using Rna Thermodynamic Properties, Jennifer A. Smith, Kay C. Wiese
Jennifer A. Smith
Covariance models are a powerful description of non-coding RNA (ncRNA) families that can be used to search nucleotide databases for new members of these ncRNA families. Currently, estimation of the parameters of a covariance model (state transition and emission scores) is based only on the observed frequencies of mutations, insertions, and deletions in known ncRNA sequences. For families with very few known members, this can result in rather uninformative models where the consensus sequence has a good score and most deviations from consensus have a fairly uniform poor score. It is proposed here to combine the traditional observed-frequency information with …