  This paper introduces a novel toolbox named BIDEAL for the generation of
biclusters, their analysis, visualization, and validation. The objective is to
facilitate researchers to use forefront biclustering algorithms embedded on a
single platform. A single toolbox comprising various biclustering algorithms
play a vital role to extract meaningful patterns from the data for detecting
diseases, biomarkers, gene-drug association, etc. BIDEAL consists of seventeen
biclustering algorithms, three biclusters visualization techniques, and six
validation indices. The toolbox can analyze several types of data, including
biological data through a graphical user interface. It also facilitates data
preprocessing techniques i.e., binarization, discretization, normalization,
elimination of null and missing values. The effectiveness of the developed
toolbox has been presented through testing and validations on Saccharomyces
cerevisiae cell cycle, Leukemia cancer, Mammary tissue profile, and Ligand
screen in B-cells datasets. The biclusters of these datasets have been
generated using BIDEAL and evaluated in terms of coherency, differential
co-expression ranking, and similarity measure. The visualization of generated
biclusters has also been provided through a heat map and gene plot.
