A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structure

  • Nyoman JuniartaEmail author
  • Miguel Couceiro
  • Amedeo Napoli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11828)


In a matrix representing a numerical dataset, a bicluster is a submatrix whose cells exhibit similar behavior. Biclustering is naturally related to Formal Concept Analysis (FCA) where concepts correspond to maximal and closed biclusters in a binary dataset. In this paper, a unified characterization of biclustering algorithms is proposed using FCA and pattern structures, an extension of FCA for dealing with numbers and other complex data. Several types of biclusters – constant-column, constant-row, additive, and multiplicative – and their relation to interval pattern structures is presented.


Biclustering FCA Gene expression Pattern structures 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Université de Lorraine, CNRS, Inria, LORIANancyFrance

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