Title
RNA-MoIP: prediction of RNA secondary structure and local 3D motifs from sequence data.
Abstract
RNA structures are hierarchically organized. The secondary structure is articulated around sophisticated local three-dimensional (3D) motifs shaping the full 3D architecture of the molecule. Recent contributions have identified and organized recurrent local 3D motifs, but applications of this knowledge for predictive purposes is still in its infancy. We recently developed a computational framework, named RNA-MoIP, to reconcile RNA secondary structure and local 3D motif information available in databases. In this paper, we introduce a web service using our software for predicting RNA hybrid 2D-3D structures from sequence data only. Optionally, it can be used for (i) local 3D motif prediction or (ii) the refinement of user-defined secondary structures. Importantly, our web server automatically generates a script for the MC-Sym software, which can be immediately used to quickly predict all-atom RNA 3D models. The web server is available at http://rnamoip.cs.mcgill.ca.
Year
DOI
Venue
2017
10.1093/nar/gkx429
NUCLEIC ACIDS RESEARCH
DocType
Volume
Issue
Journal
45
W1
ISSN
Citations 
PageRank 
0305-1048
1
0.40
References 
Authors
4
4
Name
Order
Citations
PageRank
Jason Yao110.40
Vladimir Reinharz210.73
François Major37224.97
Jérôme Waldispühl411116.24