Research Article: Detecting conserved secondary structures in RNA molecules using constrained structural alignment

Authors:
Mugdha Khaladkar;Vandanaben Patel;Vivian Bellofatto;Jeffrey Wilusz;Jason T. L. Wang
Affiliations:
Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA;Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA;Department of Microbiology and Molecular Genetics, University of Medicine and Dentistry of New Jersey-New Jersey Medical School, International Center for Public Health, 225 Warren Street, Newark, ...;Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA;Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA and Department of Microbiology and Molecular Genetics, University of Medicine a ...
Venue:
Computational Biology and Chemistry
Year:
2008

Citing 6
Cited 0

An Algorithm for Finding the Largest Approximately Common Substructures of Two Trees

IEEE Transactions on Pattern Analysis and Machine Intelligence
Rapid Assessment of Extremal Statistics for Gapped Local Alignment

Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Local Similarity in RNA Secondary Structures

CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Pure Multiple RNA Secondary Structure Alignments: A Progressive Profile Approach

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A memory-efficient algorithm for multiple sequence alignment with constraints

Bioinformatics
CMfinder---a covariance model based RNA motif finding algorithm

Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Constrained sequence alignment has been studied extensively in the past. Different forms of constraints have been investigated, where a constraint can be a subsequence, a regular expression, or a probability matrix of symbols and positions. However, constrained structural alignment has been investigated to a much lesser extent. In this paper, we present an efficient method for constrained structural alignment and apply the method to detecting conserved secondary structures, or structural motifs, in a set of RNA molecules. The proposed method combines both sequence and structural information of RNAs to find an optimal local alignment between two RNA secondary structures, one of which is a query and the other is a subject structure in the given set. The method allows a biologist to annotate conserved regions, or constraints, in the query RNA structure and incorporates these regions into the alignment process to obtain biologically more meaningful alignment scores. A statistical measure is developed to assess the significance of the scores. Experimental results based on detecting internal ribosome entry sites in the RNA molecules of hepatitis C virus and Trypanosoma brucei demonstrate the effectiveness of the proposed method and its superiority over existing techniques.