A Framework to Analyze Biclustering Results on Microarray Experiments

Microarray technology produces large amounts of information to be manipulated by analysis methods, such as biclustering algorithms, to extract new knowledge. All-purpose multivariate data visualization tools are usually not enough for studying microarray experiments. Additionally, clustering tools do not provide means of simultaneous visualization of all the biclusters obtained. We present an interactive tool that integrates traditional visualization techniques with others related to bioinformatics, such as transcription regulatory networks and microarray heatmaps, to provide enhanced understanding of the biclustering results. Our aim is to gain insight about the structure of biological data and the behavior of different biclustering algorithms.