Network compression as a quality measure for protein interaction networks.

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressibl...

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Autores principales:	Loic Royer, Matthias Reimann, A Francis Stewart, Michael Schroeder
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0e032ae04e654c28b393f5b313cb86a9
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id	oai:doaj.org-article:0e032ae04e654c28b393f5b313cb86a9
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spelling	oai:doaj.org-article:0e032ae04e654c28b393f5b313cb86a92021-11-18T07:15:19ZNetwork compression as a quality measure for protein interaction networks.1932-620310.1371/journal.pone.0035729https://doaj.org/article/0e032ae04e654c28b393f5b313cb86a92012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22719828/?tool=EBIhttps://doaj.org/toc/1932-6203With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.Loic RoyerMatthias ReimannA Francis StewartMichael SchroederPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 6, p e35729 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Loic Royer Matthias Reimann A Francis Stewart Michael Schroeder Network compression as a quality measure for protein interaction networks.
description	With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.
format	article
author	Loic Royer Matthias Reimann A Francis Stewart Michael Schroeder
author_facet	Loic Royer Matthias Reimann A Francis Stewart Michael Schroeder
author_sort	Loic Royer
title	Network compression as a quality measure for protein interaction networks.
title_short	Network compression as a quality measure for protein interaction networks.
title_full	Network compression as a quality measure for protein interaction networks.
title_fullStr	Network compression as a quality measure for protein interaction networks.
title_full_unstemmed	Network compression as a quality measure for protein interaction networks.
title_sort	network compression as a quality measure for protein interaction networks.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/0e032ae04e654c28b393f5b313cb86a9
work_keys_str_mv	AT loicroyer networkcompressionasaqualitymeasureforproteininteractionnetworks AT matthiasreimann networkcompressionasaqualitymeasureforproteininteractionnetworks AT afrancisstewart networkcompressionasaqualitymeasureforproteininteractionnetworks AT michaelschroeder networkcompressionasaqualitymeasureforproteininteractionnetworks
_version_	1718423708606922752

Network compression as a quality measure for protein interaction networks.

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