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Qiaonan Duan, Avi Ma'ayan (Icahn School of Medicine at Mount Sinai, New York, USA)Many high-throughput experiments produce gene lists. Interpretation of these gene lists for extraction of novel biological knowledge is challenging. Enrichment analysis is one of the most useful methods for analyzing gene lists. While there are many tools available for this purpose, most tools accept a single gene list as input. To provide a method for concurrent enrichment analysis and result visualization for multiple input gene lists, we developed Rubik, which allows users to input multiple gene lists and analyze them at once. Rubik performs enrichment analyses using customized gene set libraries and visualizes the results on multiple canvases. Canvases are used to visualize the entire gene set libraries as clustered tiles where each tile corresponds to a gene set. The brightness of a tile is used to visualize enrichment. The canvases of different gene lists are aligned side by side so users can immediately compare enrichment analysis results for multiple input gene lists. We demonstrate the usability of Rubik for contrasting different regulatory networks that become differentially activated after multiple kinase perturbations applied to the same breast cancer cell-line.