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1 Equipe Image - Laboratoire GREYC - UMR6072 GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen 2 LCMT - Laboratoire de chimie moléculaire et thioorganique

Abstract : Chemoinformatics is a well established research field concerned with the discovery of molecule-s properties through informational techniques. Computer science-s research fields mainly concerned by the chemoinformatics field are machine learning and graph theory. From this point of view, graph kernels provide a nice framework combining machine learning techniques with graph theory. Such kernels prove their efficiency on several chemoinformatics problems. This paper presents two new graph kernels applied to regression and classification problems within the chemoinformatics field. The first kernel is based on the notion of edit distance while the second is based on sub trees enumeration. Several experiments show the complementary of both approaches.

Keywords : Edit-Distance Graph Kernel Chemoinformatics

Autor: Benoit Gaüzère - Luc Brun - Didier Villemin -



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