Literature DB >> 14962931

RAG: RNA-As-Graphs database--concepts, analysis, and features.

Hin Hark Gan1, Daniela Fera, Julie Zorn, Nahum Shiffeldrim, Michael Tang, Uri Laserson, Namhee Kim, Tamar Schlick.   

Abstract

MOTIVATION: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire.
RESULTS: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. AVAILABILITY: The database is accessible on the web at http://monod.biomath.nyu.edu/rna

Mesh:

Year:  2004        PMID: 14962931     DOI: 10.1093/bioinformatics/bth084

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  38 in total

Review 1.  Computational approaches to RNA structure prediction, analysis, and design.

Authors:  Christian Laing; Tamar Schlick
Journal:  Curr Opin Struct Biol       Date:  2011-04-21       Impact factor: 6.809

2.  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

3.  Unique folding of precursor microRNAs: quantitative evidence and implications for de novo identification.

Authors:  Stanley Ng Kwang Loong; Santosh K Mishra
Journal:  RNA       Date:  2006-12-28       Impact factor: 4.942

Review 4.  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

5.  A computational proposal for designing structured RNA pools for in vitro selection of RNAs.

Authors:  Namhee Kim; Hin Hark Gan; Tamar Schlick
Journal:  RNA       Date:  2007-02-23       Impact factor: 4.942

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

Review 7.  Computational methods in noncoding RNA research.

Authors:  Ariane Machado-Lima; Hernando A del Portillo; Alan Mitchell Durham
Journal:  J Math Biol       Date:  2007-09-04       Impact factor: 2.259

8.  An extended dual graph library and partitioning algorithm applicable to pseudoknotted RNA structures.

Authors:  Swati Jain; Sera Saju; Louis Petingi; Tamar Schlick
Journal:  Methods       Date:  2019-03-27       Impact factor: 3.608

9.  bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

Authors:  Padideh Danaee; Mason Rouches; Michelle Wiley; Dezhong Deng; Liang Huang; David Hendrix
Journal:  Nucleic Acids Res       Date:  2018-06-20       Impact factor: 16.971

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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