doi:10.1093/bioinformatics/btr258

Summary: Production of high quality multiple sequence alignments of structured RNAs relies on an iterative combination of manual editing and structure prediction. An essential feature of an RNA alignment editor is the facility to mark-up the alignment based on how it matches a given secondary

they either work at the 2D level or are suitable for detecting predefined or local contiguous tertiary motifs only. Here, we describe a web server built around ARTS, a method for aligning tertiary structures of nucleic acids (both RNA and DNA). ARTS receives a pair of 3D nucleic acid structures and searches

. To make multiple alignment of RNAs available in cases, where this limitation of the standard approach is critical, we introduce a web server that provides a complete and convenient interface to the RNA structure alignment tool ‘CARNA’. This tool uniquely supports RNAs with multiple conserved structures

iPARTS is an improved web server for aligning two RNA 3D structures based on a structural alphabet (SA)-based approach. In particular, we first derive a Ramachandran-like diagram of RNAs by plotting nu-cleotides on a 2D axis using their two pseudo-torsion angles g and h. Next, we apply the affinity

-Waterman-like alignment tool in order to accurately predict miRNA targets. Dynamic programming was used to build a score matrix based on the complementarity of nucleotides in order to trace the optimal local alignments. Important parameters, such as maximum mismatches and maximum consecu-tive mismatches between mi

ABSTRACT This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a

–Waterman-like alignment tool in order to accurately predict miRNA targets. Dynamic programming was used to build a score matrix based on the complementarity of nucleotides in order to trace the optimal local alignments. Important parameters, such as maximum mismatches and maximum consecutive mismatches between mi

An algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed numerical sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit

have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via