In the modern era when data exist everywhere, Information visualization is considered as an important analytical tool to display and process data for different aspects and it is quickly being recognized as an essential part of effective research communication.
In this project for 'Data Visualization' course taught by Prof. John A. Lee at UClouvain, we were asked to provide an Information visualization dashboard to visualize a glioblastoma gene interaction dataset that includes both edges and nodes dataset separately. Furthermore, this interactional dashboard should have been designed so that it can satisfy user's needs such as:
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uploading new datasets with a specific format
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modifying the color and size of the nodes and edges according to some metrics
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depicting multiple views of the graph structure
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etc.
In order to achieve this goal, we developed a user-friendly dashboard (called BioVisualizer) with Python 3 and Dash framework for building GUI. Dash is a powerful framework built specially for creating interactive data visualization apps. In order to create a Network visualization app using Dash, we utilized Dash Cytoscape, which is a network visualization component for Dash. Moreover, as we required to apply some network algorithms such as Community Detection, Shortest-path, we used python NetworkX library. This Dashbord was designed by Nima Farnoodian and Atefeh Bahrami at EPL, Université catholique de Louvain, December 2021.
Please see the developer guide