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Automatic RNA secondary structure determination with stochastic context-free grammars

L Grate
1995 Proceedings. International Conference on Intelligent Systems for Molecular Biology  
Dynamic programming is used to recover the optimal tree made up of the best potential base pairs and to create a stochastic context-free grammar.  ...  We have developed a method for predicting the common secondary structure of large RNA multiple alignments using only the information in the alignment.  ...  At present only the search of a fixed multiple alignment and prediction of secondary structure via a stochastic context-free grammar (Sakakibara et al. 1994 ) is functional.  ... 
pmid:7584430 fatcat:odr27zv2nzhfrk5467ccqfafoy

Stochastic context-free grammars for modeling RNA

Sakakibara, Brown, Underwood, Mian, Haussler
1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences HICSS-94  
Stochastic context-free grammars (SCFGs) are used to fold, align and model a family of homologous R N A 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.  ...  One purpose of this paper is to provide an effective method for estimating a stochastic context-free grammar to model a family of RNA sequences.  ... 
doi:10.1109/hicss.1994.323568 fatcat:o6mugm6pi5fe5lisdvgxg7fr7i

Recent methods for RNA modeling using stochastic context-free grammars [chapter]

Yasubumi Sakakibara, Michael Brown, Richard Hughey, Saira Mian, Kimmen Sjölander, Rebecca C. Underwood, David Haussler
1994 Lecture Notes in Computer Science  
Recent e orts have applied stochastic context-free grammars (SCFGs) to the problems of statistical modeling, multiple alignment, discrimination and prediction of the secondary structure of RNA families  ...  Stochastic context-free grammars (SCFGs) can be applied to the problems of folding, aligning and modeling families of homologous RNA sequences.  ...  Recent e orts have applied stochastic context-free grammars (SCFGs) to the problems of statistical modeling, multiple alignment, discrimination and prediction of the secondary structure of RNA families  ... 
doi:10.1007/3-540-58094-8_25 fatcat:3qcr4fdonrax3juwoo3y4cefni

Stochastic Context-Free Grammars in Computational Biology

Yasubumi Sakakibara, Michael Brown, Rebecca C. Underwood, Saira I. Mian, David Haussler
1993 Genome Informatics Series  
These models capture the common primary and secondary structure of the sequences with a context-free grammar, much like those used to define the syntax of programming languages.  ...  Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of homologous RNA sequences.  ...  , and can reliably determine the secondary structure of new tRNA sequences.  ... 
doi:10.11234/gi1990.4.36 fatcat:xpwjlpaq7vdmfc2kfoz4tyjywa

Small subunit ribosomal RNA modeling using stochastic context-free grammars

M P Brown
2000 Proceedings. International Conference on Intelligent Systems for Molecular Biology  
We introduce a model based on stochastic context-free grammars (SCFGs) that can construct small subunit ribosomal RNA (SSU rRNA) multiple alignments.  ...  The method takes into account both primary sequence and secondary structure basepairing interactions.  ...  Acknowldgements Most of this work was done at the University of California at Santa Cruz as a PhD student in David Haussler's group and was supported with a PMMB Burroughs Wellcome fellowship.  ... 
pmid:10977066 fatcat:tp5vfrkau5c25eojilqn7n347q

Grammatically Modeling and Predicting RNA Secondary Structures

Yasuo UEMURA, Aki HASEGAWA, Satoshi KOBAYASHI, Takashi YOKOMORI
1995 Genome Informatics Series  
Tree Adjunct Grammar for RNA (TAGRNA) is a new grammatical device to model RNA secondary structures including pseudoknots.  ...  With this parser, we first try to predict secondary structures of RNA sequences which are known to form pseudoknots structures, and show prediction results which nicely match the known structures.  ...  Akiyama (Kyoto Univ.) for useful suggestions about prediction method based on free energy computation.  ... 
doi:10.11234/gi1990.6.67 fatcat:b5vsp5g2andlfi4zohevbpzjby

An optimized parsing algorithm well suited to RNA folding

F Lefebvre
1995 Proceedings. International Conference on Intelligent Systems for Molecular Biology  
The application of stochastic context-free grammars to the determination of RNA foldings allows a simple description of the sub-class of sought secondary structures, but it needs efficient parsing algorithms  ...  structures.  ...  It relies on stochastic contextfree grammars (or stochastic grammars) to model common secondary structures of a given family of RNAs.  ... 
pmid:7584441 fatcat:uasx7rllpjeppeaexlqssa44dy

Stochastic Regular Approximation of Tree Grammars and Its Application to Faster ncRNA Family Annotation

Kazuya Ogasawara, Satoshi Kobayashi
2007 IPSJ Digital Courier  
Recently, Weinberg and Ruzzo proposed a method of approximating stochastic context free grammar by stochastic regular grammar and applied it to faster genome annotation of non-coding RNA families.  ...  Tree Adjoining Grammar (TAG) is a useful grammatical tool to model RNA secondary structures containing pseudoknots, but its time complexity for parsing is not small enough for the practical use.  ...  Covariance Model 7), 24) , CM for short, is one of the most successful grammatical model for RNA families, in which stochastic context free grammar is used to model RNA primary and secondary structures  ... 
doi:10.2197/ipsjdc.3.746 fatcat:5hpy3aoryvay5ketu6m4lqosny

RNA modeling using Gibbs sampling and stochastic context free grammars

L Grate, M Herbster, R Hughey, D Haussler, I S Mian, H Noller
1994 Proceedings. International Conference on Intelligent Systems for Molecular Biology  
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.  ...  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  ...  Recent efforts have applied Stochastic Context-Free Grammars (SCFGs) to the problems of statistical modeling, multiple alignment, discrimination and prediction of the secondary structure of RNA families  ... 
pmid:7584383 fatcat:u4tlmcrgyffvdetmox2c5wiaby

Stochastic context-free grammers for tRNA modeling

Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood, David Haussler
1994 Nucleic Acids Research  
Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of tRNA sequences.  ...  of other kinds, can find secondary structure of new tRNA sequences, and can produce multiple alignments of large sets of tRNA sequences.  ...  Readers may obtain this paper, its data and multiple alignments, and related papers via anonymous ftp from ftp.cse.ucsc.edu in /pub/rna.  ... 
doi:10.1093/nar/22.23.5112 pmid:7800507 pmcid:PMC523785 fatcat:7xjrfgubpvbi7hpmps7chvnhsa

GenRGenS: software for generating random genomic sequences and structures

Y. Ponty, M. Termier, A. Denise
2006 Bioinformatics  
GenRGenS is the only program that can handle weighted context-free grammars, thus allowing the user to model and to generate structured objects (such as RNA secondary structures) of any given desired size  ...  It handles several classes of models useful for sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions and PROSITE expressions.  ...  ACKNOWLEDGEMENTS This work was partially supported by the French IMPG and 'ACI IMPBio' programs, and the CNRS Specific Action 'Modélisation et Algorithmique des Structures d'ARN'.  ... 
doi:10.1093/bioinformatics/btl113 pmid:16574695 fatcat:3w7zvylprzev5c4l2cg7e634om

Evolving stochastic context--free grammars for RNA secondary structure prediction

James WJ Anderson, Paula Tataru, Joe Staines, Jotun Hein, Rune Lyngsø
2012 BMC Bioinformatics  
Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s.  ...  The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few intuitively designed grammars have remained dominant.  ...  Stochastic Context Free Grammars A context-free grammar G (henceforth abbreviated to "grammar") is a 4-tuple (N, V, P, S) consisting of a finite *Correspondence: anderson@stats.ox.ac.uk 1 Department of  ... 
doi:10.1186/1471-2105-13-78 pmid:22559985 pmcid:PMC3464655 fatcat:akhulwsdivh5baiavi2btu4ara

IDENTIFYING GOOD PREDICTIONS OF RNA SECONDARY STRUCTURE

M. E. NEBEL
2003 Biocomputing 2004  
In this paper we present results on the expected structural behavior of LSU rRNA derived using a stochastic context-free grammar and generating functions.  ...  Predicting the secondary structure of RNA molecules from the knowledge of the primary structure (the sequence of bases) is still a challenging task.  ...  Besides modeling a secondary structure as a planar graph, it is a slightly different approach to model it by using stochastic context-free grammars as proposed by. 14 A stochastic context-free grammar  ... 
doi:10.1142/9789812704856_0040 fatcat:yqw45bvvpjcxxjtx24bfq6yb3e

Corpus based learning of stochastic, context-free grammars combined with Hidden Markov Models for tRNA modelling

Juan Miguel Garcia Gomez, Jose Miguel Benedi, Javier Vicente, Montserrat Robles
2005 International Journal of Bioinformatics Research and Applications  
Corpus based learning of stochastic, context-free grammars combined with Hidden Markov Models for tRNA modelling.  ...  This method is based on the combination of Stochastic Context-Free Grammars (SCFG) and Hidden Markov Models (HMM).  ...  The grammar is reset-free, A → αBβ and A → αCβ in P implies B = C The first step of the Sakakibara algorithm creates context-free rules for every internal node of the trees in the samples.  ... 
doi:10.1504/ijbra.2005.007908 pmid:18048138 fatcat:u3vtz3vyqbemvew6lwmirb5b4q

Computational RNA Structure Prediction

Marc Marti-Renom, Emidio Capriotti
2008 Current Bioinformatics  
In this review, we outline the general principles that govern RNA structure and describe the databases and algorithms for analyzing and predicting RNA secondary and tertiary structure.  ...  The view of RNA as simple information transfer molecule has been continuously challenged since the discovery of ribozymes, a class of RNA molecules with enzyme-like function.  ...  Stemloc: a comparative RNA-structure finder that uses accelerated pairwise stochastic context-free grammars. http://biowiki.org/dart.  ... 
doi:10.2174/157489308783329823 fatcat:rpo3hjt2nzgkzdgkhumwz7kmou
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