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Full-Text Articles in Engineering
Integrating Thermodynamic And Observed-Frequency Data For Non-Coding Rna Gene Search, Jennifer Smith, Kay Wiese
Integrating Thermodynamic And Observed-Frequency Data For Non-Coding Rna Gene Search, Jennifer Smith, Kay Wiese
Jennifer A. Smith
Among the most powerful and commonly used methods for finding new members of non-coding RNA gene families in genomic data are covariance models. The parameters of these models are estimated from the observed position-specific frequencies of insertions, deletions, and mutations in a multiple alignment of known non-coding RNA family members. Since the vast majority of positions in the multiple alignment have no observed changes, yet there is no reason to rule them out, some form of prior is applied to the estimate. Currently, observed-frequency priors are generated from non-family members based on model node type and child node type allowing …
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 …