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A methodology for detecting the orthology signal in a PPI network at a functional complex level

BACKGROUND: Stable evolutionary signal has been observed in a yeast protein-protein interaction (PPI) network. These finding suggests more connected regions of a PPI network to be potential mediators of evolutionary information. Because more connected regions of PPI networks contain functional compl...

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Autores principales: Jancura, Pavol, Mavridou, Eleftheria, Carrillo-de Santa Pau, Enrique, Marchiori, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314571/
https://www.ncbi.nlm.nih.gov/pubmed/22759423
http://dx.doi.org/10.1186/1471-2105-13-S10-S18
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author Jancura, Pavol
Mavridou, Eleftheria
Carrillo-de Santa Pau, Enrique
Marchiori, Elena
author_facet Jancura, Pavol
Mavridou, Eleftheria
Carrillo-de Santa Pau, Enrique
Marchiori, Elena
author_sort Jancura, Pavol
collection PubMed
description BACKGROUND: Stable evolutionary signal has been observed in a yeast protein-protein interaction (PPI) network. These finding suggests more connected regions of a PPI network to be potential mediators of evolutionary information. Because more connected regions of PPI networks contain functional complexes, we are motivated to exploit the orthology relation for identifying complexes that can be clearly attributed to such evolutionary signal. RESULTS: We proposed a computational methodology for detecting the orthology signal present in a PPI network at a functional complex level. Specifically, we examined highly functionally coherent putative protein complexes as detected by a clustering technique in the complete yeast PPI network, in the yeast sub-network which spans only ortholog proteins as determined by a given second organism, and in yeast sub-networks induced by a set of proteins randomly selected. We proposed a filtering technique for extracting orthology-driven clusters with unique functionalities, that is, neither enriched by clusters identified using the complete yeast PPI network nor identified using random sampling. Moreover, we extracted functional categories that can be clearly attributed to the presence of evolutionary signal as described by these clusters. CONCLUSIONS: Application of the proposed methodology to the yeast PPI network indicated that evolutionary information at a functional complex level can be retrieved from the structure of the network. In particular, we detected protein complexes whose functionality could be uniquely attributed to the evolutionary signal. Moreover, we identified functions that are over-represented in these complexes due the evolutionary signal.
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spelling pubmed-33145712012-04-02 A methodology for detecting the orthology signal in a PPI network at a functional complex level Jancura, Pavol Mavridou, Eleftheria Carrillo-de Santa Pau, Enrique Marchiori, Elena BMC Bioinformatics Proceedings BACKGROUND: Stable evolutionary signal has been observed in a yeast protein-protein interaction (PPI) network. These finding suggests more connected regions of a PPI network to be potential mediators of evolutionary information. Because more connected regions of PPI networks contain functional complexes, we are motivated to exploit the orthology relation for identifying complexes that can be clearly attributed to such evolutionary signal. RESULTS: We proposed a computational methodology for detecting the orthology signal present in a PPI network at a functional complex level. Specifically, we examined highly functionally coherent putative protein complexes as detected by a clustering technique in the complete yeast PPI network, in the yeast sub-network which spans only ortholog proteins as determined by a given second organism, and in yeast sub-networks induced by a set of proteins randomly selected. We proposed a filtering technique for extracting orthology-driven clusters with unique functionalities, that is, neither enriched by clusters identified using the complete yeast PPI network nor identified using random sampling. Moreover, we extracted functional categories that can be clearly attributed to the presence of evolutionary signal as described by these clusters. CONCLUSIONS: Application of the proposed methodology to the yeast PPI network indicated that evolutionary information at a functional complex level can be retrieved from the structure of the network. In particular, we detected protein complexes whose functionality could be uniquely attributed to the evolutionary signal. Moreover, we identified functions that are over-represented in these complexes due the evolutionary signal. BioMed Central 2012-06-25 /pmc/articles/PMC3314571/ /pubmed/22759423 http://dx.doi.org/10.1186/1471-2105-13-S10-S18 Text en Copyright ©2012 Jancura et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Jancura, Pavol
Mavridou, Eleftheria
Carrillo-de Santa Pau, Enrique
Marchiori, Elena
A methodology for detecting the orthology signal in a PPI network at a functional complex level
title A methodology for detecting the orthology signal in a PPI network at a functional complex level
title_full A methodology for detecting the orthology signal in a PPI network at a functional complex level
title_fullStr A methodology for detecting the orthology signal in a PPI network at a functional complex level
title_full_unstemmed A methodology for detecting the orthology signal in a PPI network at a functional complex level
title_short A methodology for detecting the orthology signal in a PPI network at a functional complex level
title_sort methodology for detecting the orthology signal in a ppi network at a functional complex level
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314571/
https://www.ncbi.nlm.nih.gov/pubmed/22759423
http://dx.doi.org/10.1186/1471-2105-13-S10-S18
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