Dominant Set Biclustering

  • Matteo DenittoEmail author
  • Manuele Bicego
  • Alessandro Farinelli
  • Marcello Pelillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)


Biclustering, which can be defined as the simultaneous clustering of rows and columns in a data matrix, has received increasing attention in recent years, being applied in many scientific scenarios (e.g. bioinformatics, text analysis, computer vision). This paper proposes a novel biclustering approach, which extends the dominant-set clustering algorithm to the biclustering case. In particular, we propose a new way of representing the problem, encoded as a graph, which allows to exploit dominant set to analyse both rows and columns simultaneously. The proposed approach has been tested by using a well known synthetic microarray benchmark, with encouraging results.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Matteo Denitto
    • 1
    Email author
  • Manuele Bicego
    • 1
  • Alessandro Farinelli
    • 1
  • Marcello Pelillo
    • 2
  1. 1.Department of Computer ScienceUniversity of VeronaVeronaItaly
  2. 2.ECLT - University of VeniceVeniceItaly

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