A toolbox for bicluster analysis in R. biclust: BiCluster Algorithms. The main function biclust provides several algorithms to find biclusters in two-dimensional data: Cheng and Church, Spectral, Plaid Model, Xmotifs and Bimax. In addition, the package provides methods for data preprocessing (normalization and discretisation), visualisation, and validation of bicluster solutions.

References in zbMATH (referenced in 12 articles )

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  1. Nishchal K. Verma, T. Sharma, S. Dixit, P. Agrawal, S. Sengupta, V. Singh: BIDEAL: A Toolbox for Bicluster Analysis - Generation, Visualization and Validation (2020) arXiv
  2. François Role, Stanislas Morbieu, Mohamed Nadif: CoClust: A Python Package for Co-Clustering (2019) not zbMATH
  3. Jacques, Julien; Biernacki, Christophe: Model-based co-clustering for ordinal data (2018)
  4. Guillermo Vinué: Anthropometry: An R Package for Analysis of Anthropometric Data (2017) not zbMATH
  5. Martella, Francesca; Alfò, Marco: A finite mixture approach to joint clustering of individuals and multivariate discrete outcomes (2017)
  6. Parmeet Bhatia and Serge Iovleff and Gérard Govaert: blockcluster: An R Package for Model-Based Co-Clustering (2017) not zbMATH
  7. Kasim, Adetayo (ed.); Shkedy, Ziv (ed.); Kaiser, Sebastian (ed.); Hochreiter, Sepp (ed.); Talloen, Willem (ed.): Applied biclustering methods for big and high-dimensional data using R (2016)
  8. Fowler, Anna; Heard, Nicholas A.: On two-way Bayesian agglomerative clustering of gene expression data (2012)
  9. Wyse, Jason; Friel, Nial: Block clustering with collapsed latent block models (2012)
  10. Brusco, Michael; Steinley, Douglas: A tabu-search heuristic for deterministic two-mode blockmodeling of binary network matrices (2011)
  11. Izenman, Alan J.; Harris, Philip W.; Mennis, Jeremy; Jupin, Joseph; Obradovic, Zoran: Local spatial biclustering and prediction of urban juvenile delinquency and recidivism (2011)
  12. Lee, Youngrok; Lee, Jeonghwa; Jun, Chi-Hyuck: Stability-based validation of bicluster solutions (2011)