BIOINFORMATICS BicAT: A Biclustering Analysis Toolbox

Summary: Besides classical clustering methods such as hierarchical cluste-ring, in recent years biclustering has become a popular approach to analyze biological data sets, e.g., gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques in terms of a com-mon graphical user interface. Furthermore, BicAT provides different facilities for data preparation, inspection, and postprocessing such as discretization, filtering of biclusters according to specific criteria, or gene pair analysis for constructing gene interconnection graphs. The possibility to use different bic-lustering algorithms inside a single graphical tool allows the user to compare clustering results and choose the algorithm that best fits a specific biological scenario. The toolbox is described in the context of gene expression analy-sis, but is also applicable to other types of data, e.g., data from proteomics or synthetic lethal experiments. Availability: The BicAT toolbox is freely available a