Literature DB >> 2776449

Tree graphs of RNA secondary structures and their comparisons.

S Y Le1, R Nussinov, J V Maizel.   

Abstract

To facilitate comparison of RNA secondary structures each structure is represented as an ordered labeled tree. Several alternate secondary structures yielding a set of trees can be computed for any given RNA molecule (sequence). Frequently recurring subtrees are searched in this set of trees. The consensus structure motifs are then selected and used to construct a secondary structure model of the RNA. Given the difficulties involved in RNA secondary structure calculations, this procedure may significantly improve our predictive capabilities. In addition, the change of secondary structures between two different RNA sequences is described as a transformation of ordered trees. The transferable ratio of tree A from tree B is defined as a proportion of the largest common subtrees in trees A and B occurring in tree A. The method is applied to the study of the mechanism of human alpha 1 globin pre-mRNA splicing. In the study, two tentative splicing mechanisms, A and B, with different orders of intron excision from alpha 1 globin pre-mRNA have been stimulated. A possible relationship between the structural features of the secondary structures and the order of intron excision in the pathway of precursor splicing of human alpha 1 globin is discussed.

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Year:  1989        PMID: 2776449     DOI: 10.1016/0010-4809(89)90039-6

Source DB:  PubMed          Journal:  Comput Biomed Res        ISSN: 0010-4809


  36 in total

1.  RNAmute: RNA secondary structure mutation analysis tool.

Authors:  Alexander Churkin; Danny Barash
Journal:  BMC Bioinformatics       Date:  2006-04-25       Impact factor: 3.169

2.  Deleterious mutation prediction in the secondary structure of RNAs.

Authors:  Danny Barash
Journal:  Nucleic Acids Res       Date:  2003-11-15       Impact factor: 16.971

3.  Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design.

Authors:  Hin Hark Gan; Samuela Pasquali; Tamar Schlick
Journal:  Nucleic Acids Res       Date:  2003-06-01       Impact factor: 16.971

4.  In vitro RNA random pools are not structurally diverse: a computational analysis.

Authors:  Jana Gevertz; Hin Hark Gan; Tamar Schlick
Journal:  RNA       Date:  2005-06       Impact factor: 4.942

Review 5.  The building blocks and motifs of RNA architecture.

Authors:  Neocles B Leontis; Aurelie Lescoute; Eric Westhof
Journal:  Curr Opin Struct Biol       Date:  2006-05-19       Impact factor: 6.809

6.  Using sequence signatures and kink-turn motifs in knowledge-based statistical potentials for RNA structure prediction.

Authors:  Cigdem Sevim Bayrak; Namhee Kim; Tamar Schlick
Journal:  Nucleic Acids Res       Date:  2017-05-19       Impact factor: 16.971

7.  Inverse folding with RNA-As-Graphs produces a large pool of candidate sequences with target topologies.

Authors:  Swati Jain; Yunwen Tao; Tamar Schlick
Journal:  J Struct Biol       Date:  2019-12-23       Impact factor: 2.867

8.  Large Deviations for Random Trees.

Authors:  Yuri Bakhtin; Christine Heitsch
Journal:  J Stat Phys       Date:  2008-08       Impact factor: 1.548

9.  Opportunities and Challenges in RNA Structural Modeling and Design.

Authors:  Tamar Schlick; Anna Marie Pyle
Journal:  Biophys J       Date:  2017-02-02       Impact factor: 4.033

Review 10.  New insights from cluster analysis methods for RNA secondary structure prediction.

Authors:  Emily Rogers; Christine Heitsch
Journal:  Wiley Interdiscip Rev RNA       Date:  2016-03-11       Impact factor: 9.957

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