TY - JOUR
T1 - Stochastic context-free grammers for tRNA modeling
AU - Sakakibara, Yasubumi
AU - Brown, Michael
AU - Hughey, Richard
AU - Mian, I. Saira
AU - Sjölander, Kimmen
AU - Underwood, Rebecca C.
AU - Haussler, David
N1 - Funding Information:
We thank Anders Krogh, Harry Noller and Bryn Weiser for discussions and assistance, Michael Waterman and David Searls for discussions and anonymous referees for their suggestions. We also thank Sergey Steinberg, Daniel Gautheret, Robert Cedergren, and Mathias Sprinzl for providing us with their unpublished alignments of tRNA and tRNA gene sequences (59). This work was supported by NSF grants CDA-9115268 and IRI-9123692 and NIH grant number GM17129. This material is based upon work supported under a National Science Foundation Graduate Research Fellowship.
PY - 1994/11/25
Y1 - 1994/11/25
N2 - 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 mitochdondrial tRNAs that cannot be fit into the canonical secondary structure.
AB - 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 mitochdondrial tRNAs that cannot be fit into the canonical secondary structure.
UR - http://www.scopus.com/inward/record.url?scp=0028593508&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0028593508&partnerID=8YFLogxK
U2 - 10.1093/nar/22.23.5112
DO - 10.1093/nar/22.23.5112
M3 - Article
C2 - 7800507
AN - SCOPUS:0028593508
SN - 0305-1048
VL - 22
SP - 5112
EP - 5120
JO - Nucleic acids research
JF - Nucleic acids research
IS - 23
ER -