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Nucleic Acids Res. 1994 Nov 25;22(23):5112-20.

Stochastic context-free grammars for tRNA modeling.

Author information

1
Sinsheimer Laboratories, University of California, Santa Cruz 95064.

Abstract

Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of tRNA sequences. SCFGs capture the sequences' common primary and secondary structure and generalize the hidden Markov models (HMMs) used in related work on protein and DNA. Results show that after having been trained on as few as 20 tRNA sequences from only two tRNA subfamilies (mitochondrial and cytoplasmic), the model can discern general tRNA from similar-length RNA sequences of other kinds, can find secondary structure of new tRNA sequences, and can produce multiple alignments of large sets of tRNA sequences. Our results suggest potential improvements in the alignments of the D- and T-domains in some mitochondrial tRNAs that cannot be fit into the canonical secondary structure.

PMID:
7800507
PMCID:
PMC523785
DOI:
10.1093/nar/22.23.5112
[Indexed for MEDLINE]
Free PMC Article

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