Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling

<p>Abstract</p> <p>Background</p> <p>The use of computational methods for predicting protein interaction networks will continue to grow with the number of fully sequenced genomes available. The Co-Conservation method, also known as the Phylogenetic profiles method, is a...

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Main Authors: Hunter Lawrence, Karimpour-Fard Anis, Gill Ryan T
Format: Article
Language:English
Published: BMC 2007-10-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/8/393
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spelling doaj-ecb3a809abcc4ea38c8001fbd28429c22020-11-25T01:49:47ZengBMCBMC Genomics1471-21642007-10-018139310.1186/1471-2164-8-393Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profilingHunter LawrenceKarimpour-Fard AnisGill Ryan T<p>Abstract</p> <p>Background</p> <p>The use of computational methods for predicting protein interaction networks will continue to grow with the number of fully sequenced genomes available. The Co-Conservation method, also known as the Phylogenetic profiles method, is a well-established computational tool for predicting functional relationships between proteins.</p> <p>Results</p> <p>Here, we examined how various aspects of this method affect the accuracy and topology of protein interaction networks. We have shown that the choice of reference genome influences the number of predictions involving proteins of previously unknown function, the accuracy of predicted interactions, and the topology of predicted interaction networks. We show that while such results are relatively insensitive to the <it>E</it>-value threshold used in defining homologs, predicted interactions are influenced by the similarity metric that is employed. We show that differences in predicted protein interactions are biologically meaningful, where judicious selection of reference genomes, or use of a new scoring scheme that explicitly considers reference genome relatedness, produces known protein interactions as well as predicted protein interactions involving coordinated biological processes that are not accessible using currently available databases.</p> <p>Conclusion</p> <p>These studies should prove valuable for future studies seeking to further improve phylogenetic profiling methodologies as well for efforts to efficiently employ such methods to develop new biological insights.</p> http://www.biomedcentral.com/1471-2164/8/393
collection DOAJ
language English
format Article
sources DOAJ
author Hunter Lawrence
Karimpour-Fard Anis
Gill Ryan T
spellingShingle Hunter Lawrence
Karimpour-Fard Anis
Gill Ryan T
Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
BMC Genomics
author_facet Hunter Lawrence
Karimpour-Fard Anis
Gill Ryan T
author_sort Hunter Lawrence
title Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
title_short Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
title_full Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
title_fullStr Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
title_full_unstemmed Investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
title_sort investigation of factors affecting prediction of protein-protein interaction networks by phylogenetic profiling
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2007-10-01
description <p>Abstract</p> <p>Background</p> <p>The use of computational methods for predicting protein interaction networks will continue to grow with the number of fully sequenced genomes available. The Co-Conservation method, also known as the Phylogenetic profiles method, is a well-established computational tool for predicting functional relationships between proteins.</p> <p>Results</p> <p>Here, we examined how various aspects of this method affect the accuracy and topology of protein interaction networks. We have shown that the choice of reference genome influences the number of predictions involving proteins of previously unknown function, the accuracy of predicted interactions, and the topology of predicted interaction networks. We show that while such results are relatively insensitive to the <it>E</it>-value threshold used in defining homologs, predicted interactions are influenced by the similarity metric that is employed. We show that differences in predicted protein interactions are biologically meaningful, where judicious selection of reference genomes, or use of a new scoring scheme that explicitly considers reference genome relatedness, produces known protein interactions as well as predicted protein interactions involving coordinated biological processes that are not accessible using currently available databases.</p> <p>Conclusion</p> <p>These studies should prove valuable for future studies seeking to further improve phylogenetic profiling methodologies as well for efforts to efficiently employ such methods to develop new biological insights.</p>
url http://www.biomedcentral.com/1471-2164/8/393
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