Biyolojik ağların interaktif görselleştirilmesi için crossbar web servisinin implementasyonu

Existing computational tools, resources, and services to assist experimental biomedical research lack data diversity and data connectivity and therefore, they are limited in helping to solve real world problems. Within the framework of CROssBAR project aiming for drug discovery, CROssBAR database (CROssBAR-DB) integrated diverse biomedical resources with the predictions of a comprehensive computing resource developed using machine learning and deep learning-based methods. It is crucial for the users to perform easily search on CROssBAR-DB, and then to visualize the result of the search. For this reason, CrossBAR web service (CROssBAR-WS) is designed, developed and implemented within the scope of this thesis. In CROssBAR-WS, knowledge graphs can be generated by using the open-source graph library Cytoscape.js. CROssBAR-WS is available at crossbar.kansil.org.