Cargando…

Decomposing PPI networks for complex discovery

BACKGROUND: Protein complexes are important for understanding principles of cellular organization and functions. With the availability of large amounts of high-throughput protein-protein interactions (PPI), many algorithms have been proposed to discover protein complexes from PPI networks. However,...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Guimei, Yong, Chern Han, Chua, Hon Nian, Wong, Limsoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3289076/
https://www.ncbi.nlm.nih.gov/pubmed/22165860
http://dx.doi.org/10.1186/1477-5956-9-S1-S15
_version_ 1782224845737558016
author Liu, Guimei
Yong, Chern Han
Chua, Hon Nian
Wong, Limsoon
author_facet Liu, Guimei
Yong, Chern Han
Chua, Hon Nian
Wong, Limsoon
author_sort Liu, Guimei
collection PubMed
description BACKGROUND: Protein complexes are important for understanding principles of cellular organization and functions. With the availability of large amounts of high-throughput protein-protein interactions (PPI), many algorithms have been proposed to discover protein complexes from PPI networks. However, existing algorithms generally do not take into consideration the fact that not all the interactions in a PPI network take place at the same time. As a result, predicted complexes often contain many spuriously included proteins, precluding them from matching true complexes. RESULTS: We propose two methods to tackle this problem: (1) The localization GO term decomposition method: We utilize cellular component Gene Ontology (GO) terms to decompose PPI networks into several smaller networks such that the proteins in each decomposed network are annotated with the same cellular component GO term. (2) The hub removal method: This method is based on the observation that hub proteins are more likely to fuse clusters that correspond to different complexes. To avoid this, we remove hub proteins from PPI networks, and then apply a complex discovery algorithm on the remaining PPI network. The removed hub proteins are added back to the generated clusters afterwards. We tested the two methods on the yeast PPI network downloaded from BioGRID. Our results show that these methods can improve the performance of several complex discovery algorithms significantly. Further improvement in performance is achieved when we apply them in tandem. CONCLUSIONS: The performance of complex discovery algorithms is hindered by the fact that not all the interactions in a PPI network take place at the same time. We tackle this problem by using localization GO terms or hubs to decompose a PPI network before complex discovery, which achieves considerable improvement.
format Online
Article
Text
id pubmed-3289076
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-32890762012-02-29 Decomposing PPI networks for complex discovery Liu, Guimei Yong, Chern Han Chua, Hon Nian Wong, Limsoon Proteome Sci Proceedings BACKGROUND: Protein complexes are important for understanding principles of cellular organization and functions. With the availability of large amounts of high-throughput protein-protein interactions (PPI), many algorithms have been proposed to discover protein complexes from PPI networks. However, existing algorithms generally do not take into consideration the fact that not all the interactions in a PPI network take place at the same time. As a result, predicted complexes often contain many spuriously included proteins, precluding them from matching true complexes. RESULTS: We propose two methods to tackle this problem: (1) The localization GO term decomposition method: We utilize cellular component Gene Ontology (GO) terms to decompose PPI networks into several smaller networks such that the proteins in each decomposed network are annotated with the same cellular component GO term. (2) The hub removal method: This method is based on the observation that hub proteins are more likely to fuse clusters that correspond to different complexes. To avoid this, we remove hub proteins from PPI networks, and then apply a complex discovery algorithm on the remaining PPI network. The removed hub proteins are added back to the generated clusters afterwards. We tested the two methods on the yeast PPI network downloaded from BioGRID. Our results show that these methods can improve the performance of several complex discovery algorithms significantly. Further improvement in performance is achieved when we apply them in tandem. CONCLUSIONS: The performance of complex discovery algorithms is hindered by the fact that not all the interactions in a PPI network take place at the same time. We tackle this problem by using localization GO terms or hubs to decompose a PPI network before complex discovery, which achieves considerable improvement. BioMed Central 2011-10-14 /pmc/articles/PMC3289076/ /pubmed/22165860 http://dx.doi.org/10.1186/1477-5956-9-S1-S15 Text en Copyright ©2011 Liu 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
Liu, Guimei
Yong, Chern Han
Chua, Hon Nian
Wong, Limsoon
Decomposing PPI networks for complex discovery
title Decomposing PPI networks for complex discovery
title_full Decomposing PPI networks for complex discovery
title_fullStr Decomposing PPI networks for complex discovery
title_full_unstemmed Decomposing PPI networks for complex discovery
title_short Decomposing PPI networks for complex discovery
title_sort decomposing ppi networks for complex discovery
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3289076/
https://www.ncbi.nlm.nih.gov/pubmed/22165860
http://dx.doi.org/10.1186/1477-5956-9-S1-S15
work_keys_str_mv AT liuguimei decomposingppinetworksforcomplexdiscovery
AT yongchernhan decomposingppinetworksforcomplexdiscovery
AT chuahonnian decomposingppinetworksforcomplexdiscovery
AT wonglimsoon decomposingppinetworksforcomplexdiscovery