RNA modeling using Gibbs sampling and stochastic context free grammars.

L Grate; M Herbster; R Hughey; D Haussler; I S Mian; H Noller

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PubMed · 7584383

RNA modeling using Gibbs sampling and stochastic context free grammars.

L Grate·M Herbster·R Hughey·D Haussler·I S Mian·H Noller

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Abstract

A new method of discovering the common secondary structure of a family of homologous RNA sequences using Gibbs sampling and stochastic context-free grammars is proposed. Given an unaligned set of sequences, a Gibbs sampling step simultaneously estimates the secondary structure of each sequence and a set of statistical parameters describing the common secondary structure of the set as a whole. These parameters describe a statistical model of the family. After the Gibbs sampling has produced a crude statistical model for the family, this model is translated into a stochastic context-free grammar, which is then refined by an Expectation Maximization (EM) procedure to produce a more complete model. A prototype implementation of the method is tested on tRNA, pieces of 16S rRNA and on U5 snRNA with good results.

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Animals Base Sequence Humans Models, Theoretical Molecular Sequence Data Molecular Structure RNA Stochastic Processes Journal Article Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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L Grate, M Herbster, R Hughey, D Haussler, I S Mian, H Noller. 1994. RNA modeling using Gibbs sampling and stochastic context free grammars.. https://pubmed.ncbi.nlm.nih.gov/7584383/

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