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Pattern Structures for Identifying Biclusters with Coherent Sign Changes

Nyoman Juniarta 1 Victor Codocedo 2 Miguel Couceiro 1 Mehdi Kaytoue 2 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In this paper we are studying the task of nding coherent-sign-changes biclusters in a binary matrix. This task can be applied to the interpretation of gene expression data, where such a bicluster represents a set of experiments that aect a set of genes in a consistent way. We start with a binary table and study biclustering methods based on FCA and partition pattern structures. Pattern concepts provide biclusters and their hierarchical relation, which can be used to analyze the prole of genes in the given expression data. Our approach is purely symbolic, so we can detect larger biclusters and work with rather complex data.
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Contributor : Nyoman Juniarta <>
Submitted on : Thursday, June 27, 2019 - 10:12:31 AM
Last modification on : Thursday, January 9, 2020 - 12:17:25 PM


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  • HAL Id : hal-02166713, version 1


Nyoman Juniarta, Victor Codocedo, Miguel Couceiro, Mehdi Kaytoue, Amedeo Napoli. Pattern Structures for Identifying Biclusters with Coherent Sign Changes. Diana Cristea; Florence ; Rokia Missaoui; Léonard Kwuida; Barış Sertkaya. ICFCA 2019 - 15th International Conference on Formal Concept Analysis, Jun 2019, Frankfurt, Germany. Proceedings of the 15th International Conference on Formal Concept Analysis (Supplementary Proceedings). ⟨hal-02166713⟩



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