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Fouille de motifs séquentiels pour la découverte de relations entre gènes et maladies rares

Nicolas Béchet 1 Peggy Cellier 2 Thierry Charnois 3 Bruno Crémilleux 4
1 EXPRESSION - Expressiveness in Human Centered Data/Media
UBS - Université de Bretagne Sud, IRISA-D6 - MEDIA ET INTERACTIONS
2 LIS - Logical Information Systems
4 Equipe CODAG - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : Orphanet provides an international web-based knowledge portal for rare diseases including a collection of review articles. However, reviews and literature monitoring are manual. Thus, new documentation about a rare disease is a time-consuming process and automatically discovering knowledge from a large collection of texts is a crucial issue. This context represents a strong motivation to address the problem of extracting gene–rare diseases relationships from texts. In this paper, we tackle this issue with a cross-fertilization of information extraction and data mining techniques (sequential pattern mining under constraints). Experiments show the interest of the method for the documentation of rare diseases.
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Submitted on : Monday, February 23, 2015 - 2:15:21 PM
Last modification on : Wednesday, October 27, 2021 - 2:54:59 PM


  • HAL Id : hal-01119525, version 1


Nicolas Béchet, Peggy Cellier, Thierry Charnois, Bruno Crémilleux. Fouille de motifs séquentiels pour la découverte de relations entre gènes et maladies rares. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2014, 28/2-3, pp.245-270. ⟨hal-01119525⟩



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