An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.

Graphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually finding all graphl...

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Main Authors: Ine Melckenbeeck, Pieter Audenaert, Tom Michoel, Didier Colle, Mario Pickavet
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0147078
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spelling doaj-b787af52445e42a2a045ecd402f5c8002021-03-04T12:32:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01111e014707810.1371/journal.pone.0147078An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.Ine MelckenbeeckPieter AudenaertTom MichoelDidier ColleMario PickavetGraphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually finding all graphlets in a large graph can be time-consuming, however. As the graphlets grow in size, more different graphlets emerge and the time needed to find each graphlet also scales up. If it is not needed to find each instance of each graphlet, but knowing the number of graphlets touching each node of the graph suffices, the problem is less hard. Previous research shows a way to simplify counting the graphlets: instead of looking for the graphlets needed, smaller graphlets are searched, as well as the number of common neighbors of vertices. Solving a system of equations then gives the number of times a vertex is part of each graphlet of the desired size. However, until now, equations only exist to count graphlets with 4 or 5 nodes. In this paper, two new techniques are presented. The first allows to generate the equations needed in an automatic way. This eliminates the tedious work needed to do so manually each time an extra node is added to the graphlets. The technique is independent on the number of nodes in the graphlets and can thus be used to count larger graphlets than previously possible. The second technique gives all graphlets a unique ordering which is easily extended to name graphlets of any size. Both techniques were used to generate equations to count graphlets with 4, 5 and 6 vertices, which extends all previous results. Code can be found at https://github.com/IneMelckenbeeck/equation-generator and https://github.com/IneMelckenbeeck/graphlet-naming.https://doi.org/10.1371/journal.pone.0147078
collection DOAJ
language English
format Article
sources DOAJ
author Ine Melckenbeeck
Pieter Audenaert
Tom Michoel
Didier Colle
Mario Pickavet
spellingShingle Ine Melckenbeeck
Pieter Audenaert
Tom Michoel
Didier Colle
Mario Pickavet
An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
PLoS ONE
author_facet Ine Melckenbeeck
Pieter Audenaert
Tom Michoel
Didier Colle
Mario Pickavet
author_sort Ine Melckenbeeck
title An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
title_short An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
title_full An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
title_fullStr An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
title_full_unstemmed An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.
title_sort algorithm to automatically generate the combinatorial orbit counting equations.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description Graphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually finding all graphlets in a large graph can be time-consuming, however. As the graphlets grow in size, more different graphlets emerge and the time needed to find each graphlet also scales up. If it is not needed to find each instance of each graphlet, but knowing the number of graphlets touching each node of the graph suffices, the problem is less hard. Previous research shows a way to simplify counting the graphlets: instead of looking for the graphlets needed, smaller graphlets are searched, as well as the number of common neighbors of vertices. Solving a system of equations then gives the number of times a vertex is part of each graphlet of the desired size. However, until now, equations only exist to count graphlets with 4 or 5 nodes. In this paper, two new techniques are presented. The first allows to generate the equations needed in an automatic way. This eliminates the tedious work needed to do so manually each time an extra node is added to the graphlets. The technique is independent on the number of nodes in the graphlets and can thus be used to count larger graphlets than previously possible. The second technique gives all graphlets a unique ordering which is easily extended to name graphlets of any size. Both techniques were used to generate equations to count graphlets with 4, 5 and 6 vertices, which extends all previous results. Code can be found at https://github.com/IneMelckenbeeck/equation-generator and https://github.com/IneMelckenbeeck/graphlet-naming.
url https://doi.org/10.1371/journal.pone.0147078
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