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.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Ignatov, Dmitry I.; Gnatyshak, Dmitry V.; Kuznetsov, Sergei O.; Mirkin, Boris G.: Triadic formal concept analysis and triclustering: searching for optimal patterns (2015)
- Elloumi, Mourad; Zomaya, Albert Y.: Biological knowledge discovery handbook. Preprocessing, Mining and postprocessing of biological data (2014)
- Ahn, Jaegyoon; Yoon, Youngmi; Park, Sanghyun: Noise-robust algorithm for identifying functionally associated biclusters from gene expression data (2011)
- Gupta, Neelima; Aggarwal, Seema: MIB: using mutual information for biclustering gene expression data (2010)
- Symeonidis, Panagiotis; Nanopoulos, Alexandros; Papadopoulos, Apostolos N.; Manolopoulos, Yannis: Nearest-biclusters collaborative filtering based on constant and coherent values (2008)
Further publications can be found at: http://www.tik.ethz.ch/sop/bicat/?page=publications.php