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Heuristic Pairwise Alignment in Database Environments

Biological data have gained wider recognition during the last few years, although managing and processing these data in an efficient way remains a challenge in many areas. Increasingly, more DNA sequence databases can be accessed; however, most algorithms on these sequences are performed outside of...

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Autores principales: Lipták, Panna, Kiss, Attila, Szalai-Gindl, János Márk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690874/
https://www.ncbi.nlm.nih.gov/pubmed/36360242
http://dx.doi.org/10.3390/genes13112005
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author Lipták, Panna
Kiss, Attila
Szalai-Gindl, János Márk
author_facet Lipták, Panna
Kiss, Attila
Szalai-Gindl, János Márk
author_sort Lipták, Panna
collection PubMed
description Biological data have gained wider recognition during the last few years, although managing and processing these data in an efficient way remains a challenge in many areas. Increasingly, more DNA sequence databases can be accessed; however, most algorithms on these sequences are performed outside of the database with different bioinformatics software. In this article, we propose a novel approach for the comparative analysis of sequences, thereby defining heuristic pairwise alignment inside the database environment. This method takes advantage of the benefits provided by the database management system and presents a way to exploit similarities in data sets to quicken the alignment algorithm. We work with the column-oriented MonetDB, and we further discuss the key benefits of this database system in relation to our proposed heuristic approach.
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spelling pubmed-96908742022-11-25 Heuristic Pairwise Alignment in Database Environments Lipták, Panna Kiss, Attila Szalai-Gindl, János Márk Genes (Basel) Article Biological data have gained wider recognition during the last few years, although managing and processing these data in an efficient way remains a challenge in many areas. Increasingly, more DNA sequence databases can be accessed; however, most algorithms on these sequences are performed outside of the database with different bioinformatics software. In this article, we propose a novel approach for the comparative analysis of sequences, thereby defining heuristic pairwise alignment inside the database environment. This method takes advantage of the benefits provided by the database management system and presents a way to exploit similarities in data sets to quicken the alignment algorithm. We work with the column-oriented MonetDB, and we further discuss the key benefits of this database system in relation to our proposed heuristic approach. MDPI 2022-11-02 /pmc/articles/PMC9690874/ /pubmed/36360242 http://dx.doi.org/10.3390/genes13112005 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lipták, Panna
Kiss, Attila
Szalai-Gindl, János Márk
Heuristic Pairwise Alignment in Database Environments
title Heuristic Pairwise Alignment in Database Environments
title_full Heuristic Pairwise Alignment in Database Environments
title_fullStr Heuristic Pairwise Alignment in Database Environments
title_full_unstemmed Heuristic Pairwise Alignment in Database Environments
title_short Heuristic Pairwise Alignment in Database Environments
title_sort heuristic pairwise alignment in database environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690874/
https://www.ncbi.nlm.nih.gov/pubmed/36360242
http://dx.doi.org/10.3390/genes13112005
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