BIDEAL: A Toolbox for Bicluster Analysis -- Generation, Visualization and Validation

TL;DR

BIDEAL is a comprehensive toolbox that integrates multiple biclustering algorithms, visualization, and validation tools to facilitate biological data analysis and pattern discovery.

Contribution

It introduces a unified platform with 17 algorithms, visualization methods, and validation indices for bicluster analysis, supporting diverse biological data preprocessing.

Findings

Effective bicluster extraction from biological datasets

Enhanced visualization of biclusters via heat maps and gene plots

Validated on multiple biological datasets with positive results

Abstract

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.