Cargando…

Alignment-free protein interaction network comparison

Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone...

Descripción completa

Detalles Bibliográficos
Autores principales: Ali, Waqar, Rito, Tiago, Reinert, Gesine, Sun, Fengzhu, Deane, Charlotte M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147900/
https://www.ncbi.nlm.nih.gov/pubmed/25161230
http://dx.doi.org/10.1093/bioinformatics/btu447
_version_ 1782332533290041344
author Ali, Waqar
Rito, Tiago
Reinert, Gesine
Sun, Fengzhu
Deane, Charlotte M.
author_facet Ali, Waqar
Rito, Tiago
Reinert, Gesine
Sun, Fengzhu
Deane, Charlotte M.
author_sort Ali, Waqar
collection PubMed
description Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
format Online
Article
Text
id pubmed-4147900
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-41479002014-09-02 Alignment-free protein interaction network comparison Ali, Waqar Rito, Tiago Reinert, Gesine Sun, Fengzhu Deane, Charlotte M. Bioinformatics Eccb 2014 Proceedings Papers Committee Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-08-22 /pmc/articles/PMC4147900/ /pubmed/25161230 http://dx.doi.org/10.1093/bioinformatics/btu447 Text en © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 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 Eccb 2014 Proceedings Papers Committee
Ali, Waqar
Rito, Tiago
Reinert, Gesine
Sun, Fengzhu
Deane, Charlotte M.
Alignment-free protein interaction network comparison
title Alignment-free protein interaction network comparison
title_full Alignment-free protein interaction network comparison
title_fullStr Alignment-free protein interaction network comparison
title_full_unstemmed Alignment-free protein interaction network comparison
title_short Alignment-free protein interaction network comparison
title_sort alignment-free protein interaction network comparison
topic Eccb 2014 Proceedings Papers Committee
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147900/
https://www.ncbi.nlm.nih.gov/pubmed/25161230
http://dx.doi.org/10.1093/bioinformatics/btu447
work_keys_str_mv AT aliwaqar alignmentfreeproteininteractionnetworkcomparison
AT ritotiago alignmentfreeproteininteractionnetworkcomparison
AT reinertgesine alignmentfreeproteininteractionnetworkcomparison
AT sunfengzhu alignmentfreeproteininteractionnetworkcomparison
AT deanecharlottem alignmentfreeproteininteractionnetworkcomparison