TY - JOUR
T1 - RAG
T2 - RNA-As-Graphs database - Concepts, analysis, and features
AU - Gan, Hin Hark
AU - Fera, Daniela
AU - Zorn, Julie
AU - Shiffeldrim, Nahum
AU - Tang, Michael
AU - Laserson, Uri
AU - Kim, Namhee
AU - Schlick, Tamar
N1 - Funding Information:
We thank the referees for their constructive suggestions for improving RAG and Danny Banash for comments related to the use of the Laplacian second Eigen value. This work was supported by a Joint NSF/NIGMS Initiative in Mathematical Biology (DMS-0201160) as well as Human Frontier Science Program (HFSP). D.F. acknowledges support from the Dean’s Undergraduate Research Fund and a summer fellowship from the Department of Chemistry.
PY - 2004/5/22
Y1 - 2004/5/22
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/3042542464
U2 - 10.1093/bioinformatics/bth084
DO - 10.1093/bioinformatics/bth084
M3 - Article
C2 - 14962931
AN - SCOPUS:3042542464
SN - 1367-4803
VL - 20
SP - 1285
EP - 1291
JO - Bioinformatics
JF - Bioinformatics
IS - 8
ER -