Gene network interconnectedness and the generalized topological overlap measure

<p>Abstract</p> <p>Background</p> <p>Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the...

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Main Authors: Horvath Steve, Yip Andy M
Format: Article
Language:English
Published: BMC 2007-01-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/8/22
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author Horvath Steve
Yip Andy M
author_facet Horvath Steve
Yip Andy M
author_sort Horvath Steve
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the information on the connection (adjacency) between 2 nodes may be noisy or incomplete, it can be desirable to consider alternative measures of pairwise interconnectedness. Here we study a class of measures that are proportional to the number of neighbors that a pair of nodes share in common. For example, the topological overlap measure by Ravasz <it>et al</it>. <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> can be interpreted as a measure of agreement between the <it>m </it>= 1 step neighborhoods of 2 nodes. Several studies have shown that two proteins having a higher topological overlap are more likely to belong to the same functional class than proteins having a lower topological overlap. Here we address the question whether a measure of topological overlap based on higher-order neighborhoods could give rise to a more robust and sensitive measure of interconnectedness.</p> <p>Results</p> <p>We generalize the topological overlap measure from <it>m </it>= 1 step neighborhoods to <it>m </it>≥ 2 step neighborhoods. This allows us to define the <it>m</it>-th order generalized topological overlap measure (GTOM) by (i) counting the number of <it>m</it>-step neighbors that a pair of nodes share and (ii) normalizing it to take a value between 0 and 1. Using theoretical arguments, a yeast co-expression network application, and a fly protein network application, we illustrate the usefulness of the proposed measure for module detection and gene neighborhood analysis.</p> <p>Conclusion</p> <p>Topological overlap can serve as an important filter to counter the effects of spurious or missing connections between network nodes. The <it>m</it>-th order topological overlap measure allows one to trade-off sensitivity versus specificity when it comes to defining pairwise interconnectedness and network modules.</p>
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spelling doaj.art-93a18d33653d4e0b8285963900c9b69a2022-12-22T01:43:24ZengBMCBMC Bioinformatics1471-21052007-01-01812210.1186/1471-2105-8-22Gene network interconnectedness and the generalized topological overlap measureHorvath SteveYip Andy M<p>Abstract</p> <p>Background</p> <p>Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the information on the connection (adjacency) between 2 nodes may be noisy or incomplete, it can be desirable to consider alternative measures of pairwise interconnectedness. Here we study a class of measures that are proportional to the number of neighbors that a pair of nodes share in common. For example, the topological overlap measure by Ravasz <it>et al</it>. <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> can be interpreted as a measure of agreement between the <it>m </it>= 1 step neighborhoods of 2 nodes. Several studies have shown that two proteins having a higher topological overlap are more likely to belong to the same functional class than proteins having a lower topological overlap. Here we address the question whether a measure of topological overlap based on higher-order neighborhoods could give rise to a more robust and sensitive measure of interconnectedness.</p> <p>Results</p> <p>We generalize the topological overlap measure from <it>m </it>= 1 step neighborhoods to <it>m </it>≥ 2 step neighborhoods. This allows us to define the <it>m</it>-th order generalized topological overlap measure (GTOM) by (i) counting the number of <it>m</it>-step neighbors that a pair of nodes share and (ii) normalizing it to take a value between 0 and 1. Using theoretical arguments, a yeast co-expression network application, and a fly protein network application, we illustrate the usefulness of the proposed measure for module detection and gene neighborhood analysis.</p> <p>Conclusion</p> <p>Topological overlap can serve as an important filter to counter the effects of spurious or missing connections between network nodes. The <it>m</it>-th order topological overlap measure allows one to trade-off sensitivity versus specificity when it comes to defining pairwise interconnectedness and network modules.</p>http://www.biomedcentral.com/1471-2105/8/22
spellingShingle Horvath Steve
Yip Andy M
Gene network interconnectedness and the generalized topological overlap measure
BMC Bioinformatics
title Gene network interconnectedness and the generalized topological overlap measure
title_full Gene network interconnectedness and the generalized topological overlap measure
title_fullStr Gene network interconnectedness and the generalized topological overlap measure
title_full_unstemmed Gene network interconnectedness and the generalized topological overlap measure
title_short Gene network interconnectedness and the generalized topological overlap measure
title_sort gene network interconnectedness and the generalized topological overlap measure
url http://www.biomedcentral.com/1471-2105/8/22
work_keys_str_mv AT horvathsteve genenetworkinterconnectednessandthegeneralizedtopologicaloverlapmeasure
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