TIN-X is an interactive visualization tool for discovering interesting associations between diseases and potential drug targets. The tool uses natural language processing to identify disease and protein mentions in the text of PubMed abstracts. Using this data, it derives two metrics: novelty and importance. Novelty measures the relative scarcity of specific publications about a given concept (such as a target or a disease), while importance measures the relative strength of the association between two concepts. The web tool enables users to explore the relationships between the novelty of potential drug targets and their importance to diseases.


Project: App Development, User Experience, Visual Design, Cloud Deployment, Application Quality Control and Testing

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