Applications of RAG
Non-coding RNA classification
1. Karklin Y, Meraz RF, Holbrook SR: Classification of non-coding RNA using graph representations of secondary structure. Pac Symp Biocomput2005:4-15.
2. Hamada M, Tsuda K, Kudo T, Kin T, Asai K: Mining frequent stem patterns from unaligned RNA sequences. Bioinformatics2006, 22:2480-2487.
3. Machado-Lima A, del Portillo HA, Durham AM: Computational methods in noncoding RNA research. J Math Biol2008, 56:15-49.
4. Ng KLS, Mishra SK: De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures. Bioinformatics2007, 23:1321-1330.
5. Shu WJ, Bo XC, Zheng ZQ, Wang SQ: A novel representation of RNA secondary structure based on element-contact graphs. BMC Bioinformatics2008, 9:188-195.
Quantitative analysis of RNA secondary structure
1. Haynes T, Knisley D, Knisley J: Using a neural network to identify secondary RNA structures quantified by graphical invariants. Comm Math Comput Chem2008, 60:277-290.
2. Haynes T, Knisley D, Seier E, Zou Y: A quantitative analysis of secondary RNA structure using domination based parameters on trees. BMC Bioinformatics2006, 7:108-118.
3. Bon M, Vernizzi G, Orland H, Zee A: Topological classification of RNA structures. J Mol Biol2008, 379:900-911.
4. Bakhtin Y, Heitsch CE: Large deviations for random trees and the branching of RNA secondary structures. Bull Math Biol 2009, 71:84-106.
5. Hower V, Heitsch CE: Parametric Analysis of RNA Branching Configurations. Bull Math Biol 2011, doi 10.1007/s11538-010-9607-3.
6. Koessler DR, Knisley DJ, Knisley J, Haynes T: A predictive model for secondary RNA structure using graph theory and a neural network. BMC Bioinformatics 2010, 11 Suppl 6:S21.
Pseudoknot structure analysis
1. Brierley I, Pennell S, Gilbert RJC: Viral RNA pseudoknots: versatile motifs in gene expression and replication. Nat Rev Microbiol2007, 5:598-610.
2. Pennell S, Manktelow E, Flatt A, Kelly G, Smerdon SJ, Brierley I: The stimulatory RNA of the Visna-Maedi retrovirus ribosomal frameshifting signal is an unusual pseudoknot with an interstem element. RNA2008, 14:1366-1377.
3. Baird SD, Turcotte M, Korneluk RG, Holcik M: Searching for IRES. RNA2006, 12:1755-1785.
4. Rodland EA: Pseudoknots in RNA secondary structures: Representation, enumeration, and prevalence. J Comput Biol2006, 13:1197-1213.
RNA structure review papers
1. Hendrix DK, Brenner SE, Holbrook SR: RNA structural motifs: building blocks of a modular biomolecule. Q Rev Biophys2005, 38:221-243.
2. Leontis NB, Lescoute A, Westhof E: The building blocks and motifs of RNA architecture. Curr Opin Struct Biol2006, 16:279-287.
Novel RNA design
1. Kim N, Shiffeldrim N, Gan HH, Schlick T: Candidates for novel RNA topologies. J Mol Biol2004, 341:1129-1144.
2. Gan HH, Pasquali S, Schlick T: Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design. Nucleic Acids Res2003, 31:2926-2943.
3. Pasquali S, Gan HH, Schlick T: Modular RNA architecture revealed by computational analysis of existing pseudoknots and ribosomal RNAs. Nucleic Acids Res 2005, 33:1384-1398.
4. Laserson U, Gan HH, Schlick T: Predicting candidate genomic sequences that correspond to synthetic functional RNA motifs. Nucleic Acids Res 2005, 33:6057-6069.
5. Gevertz J, Gan HH, Schlick T: In vitro RNA random pools are not structurally diverse: A computational analysis. RNA 2005, 11:853-863.
6. Kim N, Gan HH, Schlick T: A computational proposal for designing structured RNA pools for in vitro selection of RNAs. RNA 2007, 13:478-492.
7. Kim N, Shin JS, Elmetwaly S, Gan HH, Schlick T: RAGPOOLS: RNA-As-Graph-Pools - a web server for assisting the design of structured RNA pools for in vitro selection. Bioinformatics 2007, 23:2959-2960.
8. Kim N, Izzo JA, Elmetwaly S, Gan HH, Schlick T: Computational generation and screening of RNA motifs in large nucleotide sequence pools. Nucleic Acids Res 2010, 38:e139.