Classes empiétantes dans un graphe et application aux interactions entre protéines

Lucile Denoeud (), Irène Charon (), Alain Guénoche () and Olivier Hudry ()
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Lucile Denoeud: ENST et CERMSEM
Irène Charon: ENST
Alain Guénoche: Institut de Mathématiques de Luminy
Olivier Hudry: ENST et CERMSEM

Cahiers de la Maison des Sciences Economiques from Université Panthéon-Sorbonne (Paris 1)

Abstract: In this paper, we study a method of classification by density in an unweighted graph. We search some areas with a high density of edges, that can be overlapping (we don't try to obtain a partition but some intrinsic classes). The method consists of two steps; first we determine the cores of the classes by means of a local density function and then we extend these cores by their neighbourhoods following a criterion on the density of the classes. Finally, the method is applied on a protein-protein interaction network, with the aim of predicting unknown cellular functions of some proteins

Keywords: Bioinformatics; classification; density function; interaction network (search for similar items in EconPapers)
JEL-codes: C69 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2005-04
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Persistent link: https://EconPapers.repec.org/RePEc:mse:wpsorb:b05032

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