Repository: Freie Universität Berlin, Math Department

LaRA 2: parallel and vectorized program for sequence–structure alignment of RNA sequences

Winkler, Jörg and Urgese, Gianvito and Ficarra, Elisa and Reinert, Knut (2022) LaRA 2: parallel and vectorized program for sequence–structure alignment of RNA sequences. BMC Bioinformatics, 23 (1). ISSN 1471-2105

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Background The function of non-coding RNA sequences is largely determined by their spatial conformation, namely the secondary structure of the molecule, formed by Watson–Crick interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural information into account. In order to discover yet unknown RNA families and infer their possible functions, the structural alignment of RNAs is an essential task. This task demands a lot of computational resources, especially for aligning many long sequences, and it therefore requires efficient algorithms that utilize modern hardware when available. A subset of the secondary structures contains overlapping interactions (called pseudoknots), which add additional complexity to the problem and are often ignored in available software. Results We present the SeqAn-based software LaRA 2 that is significantly faster than comparable software for accurate pairwise and multiple alignments of structured RNA sequences. In contrast to other programs our approach can handle arbitrary pseudoknots. As an improved re-implementation of the LaRA tool for structural alignments, LaRA 2 uses multi-threading and vectorization for parallel execution and a new heuristic for computing a lower boundary of the solution. Our algorithmic improvements yield a program that is up to 130 times faster than the previous version. Conclusions With LaRA 2 we provide a tool to analyse large sets of RNA secondary structures in relatively short time, based on structural alignment. The produced alignments can be used to derive structural motifs for the search in genomic databases.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Computer Science
Divisions:Department of Mathematics and Computer Science > Institute of Computer Science > Algorithmic Bioinformatics Group
ID Code:2695
Deposited By: Anja Kasseckert
Deposited On:02 Feb 2022 13:29
Last Modified:02 Feb 2022 13:51

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