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Visualization of Linked Biomedical Data Using Cluster Chart

With the continuous increasing of biomedical data, how to effectively use these large-scale data sets has become an urgent problem. It is also an essential issue to make benefit to users by consuming these biomedical data on the Semantic Web in a reasonable way. We present a visualization approach based on a tree-like layered interactive user interface, realize the queries of the relationships between targets, compounds, and diseases, and show the width of the path between the two biological entities according to their correlations. Furthermore, we design an iterative query method, which can find not only direct results of the input entity, but also extended results with some similarities of the input entity. Thus, the potential relationships among the extended results can be further investigated by biomedical scientists. Therefore, we have developed a user-friendly visualization system that can leverage the rich sets of the linked biomedical data.