BicAT (Biclustering Analysis Toolbox) .BicAT is a graphical user interface software for the analysis of gene expression data. It provides five biclustering and two standard clustering algorithms. BicAT works on Windows, Solaris, Linux and Mac OS. BicAT (Biclustering Analysis Toolbox) is a software tool which offers a graphical user interface for several existing biclustering and clustering algorithms. The main purpose of the tool is to help biologists with the analysis and exploration of the gene expression data, e.g. microarrays.

References in zbMATH (referenced in 16 articles )

Showing results 1 to 16 of 16.
Sorted by year (citations)

  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. Henriques, Rui; Madeira, Sara C.: Bsig: evaluating the statistical significance of biclustering solutions (2018)
  4. Martella, Francesca; Alfò, Marco: A finite mixture approach to joint clustering of individuals and multivariate discrete outcomes (2017)
  5. Parmeet Bhatia and Serge Iovleff and Gérard Govaert: blockcluster: An R Package for Model-Based Co-Clustering (2017) not zbMATH
  6. Ignatov, Dmitry I.; Gnatyshak, Dmitry V.; Kuznetsov, Sergei O.; Mirkin, Boris G.: Triadic formal concept analysis and triclustering: searching for optimal patterns (2015)
  7. Elloumi, Mourad; Zomaya, Albert Y.: Biological knowledge discovery handbook. Preprocessing, Mining and postprocessing of biological data (2014)
  8. Boutsinas, Basilis: Machine-part cell formation using biclustering (2013)
  9. Martella, Francesca; Vichi, Maurizio: Clustering microarray data using model-based double (K)-means (2012)
  10. Ahn, Jaegyoon; Yoon, Youngmi; Park, Sanghyun: Noise-robust algorithm for identifying functionally associated biclusters from gene expression data (2011) ioport
  11. Freitas, A.; Afreixo, V.; Pinheiro, M.; Oliveira, J. L.; Moura, G.; Santos, M.: Improving the performance of the iterative signature algorithm for the identification of relevant patterns (2011)
  12. Martella, F.; Alfò, M.; Vichi, M.: Hierarchical mixture models for biclustering in microarray data (2011)
  13. Gupta, Neelima; Aggarwal, Seema: MIB: using mutual information for biclustering gene expression data (2010)
  14. Symeonidis, Panagiotis; Nanopoulos, Alexandros; Papadopoulos, Apostolos N.; Manolopoulos, Yannis: Nearest-biclusters collaborative filtering based on constant and coherent values (2008) ioport
  15. Zhao, Hongya; Liew, Alan Wee-Chung; Xie, Xudong; Yan, Hong: A new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data (2008)
  16. Barkow, Simon; Bleuler, Stefan; Prelic, Amela; Zimmermann, Philip; Zitzler, Eckart: Bicat: A biclustering analysis toolbox (2006) ioport

Further publications can be found at: