Publications Current Grant: NIH R15 (AREA) grant 1R15GM087646-01, July 2009 - June 2012 Thermodynamics-inspired Improvement of RNA Search in Genomic Databases Jennifer A. Smith - Principle Investigator Improved covariance model parameter estimates using thermodynamics experimental data: Covariance models are a powerful and popular
method for searching genomic databases for new members of functional RNA
families. The use of prior information in covariance model parameter estimation
is crucial since many RNA families only have a very few known examples or all
those that are known are in a sub-family of the actual family. Experimental
thermodynamic measurements of RNA structures point to a number of regularities
in molecular stability that are not captured in current covariance modeling practice.
Among these are the dependence of stability on hairpin closing pair and loop
end nucleotide identities and well as hairpin loop length. Preliminary evidence
has been found that incorporation of these effects into priors and model
structure may improve covariance model performance. Additional thermodynamics-inspired improvements to covariance model
parameter estimation and structure, combine the prior information with
in-family observed-frequency data in an optimal fashion, and to expand testing
of the performance of the model structure changes and parameter estimation
methods. Faster covariance model search using partial covariance models: <description needed> Special-purpose computing hardware for covariance model database scoring: <description needed> |
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