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CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways
Motivation: Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellula...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694646/ https://www.ncbi.nlm.nih.gov/pubmed/23812978 http://dx.doi.org/10.1093/bioinformatics/btt235 |
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author | Abaka, Gamze Bıyıkoğlu, Türker Erten, Cesim |
author_facet | Abaka, Gamze Bıyıkoğlu, Türker Erten, Cesim |
author_sort | Abaka, Gamze |
collection | PubMed |
description | Motivation: Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. Results: We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Availability: Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Contact: cesim@khas.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3694646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36946462013-06-27 CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways Abaka, Gamze Bıyıkoğlu, Türker Erten, Cesim Bioinformatics Ismb/Eccb 2013 Proceedings Papers Committee July 21 to July 23, 2013, Berlin, Germany Motivation: Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. Results: We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Availability: Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Contact: cesim@khas.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2013-07-01 2013-06-19 /pmc/articles/PMC3694646/ /pubmed/23812978 http://dx.doi.org/10.1093/bioinformatics/btt235 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Ismb/Eccb 2013 Proceedings Papers Committee July 21 to July 23, 2013, Berlin, Germany Abaka, Gamze Bıyıkoğlu, Türker Erten, Cesim CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title | CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title_full | CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title_fullStr | CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title_full_unstemmed | CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title_short | CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
title_sort | campways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways |
topic | Ismb/Eccb 2013 Proceedings Papers Committee July 21 to July 23, 2013, Berlin, Germany |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694646/ https://www.ncbi.nlm.nih.gov/pubmed/23812978 http://dx.doi.org/10.1093/bioinformatics/btt235 |
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