- shinyDeepDR is a web tool for predicting responses to 265 anti-cancer compounds
- It is applicable for researching both cancer cell lines and tumors
- Its interactive web interface facilitates result interpretation and investigation
- It identifies promising targets for an “undruggable” mutation in liver cancer
The bigger picture
Understanding how different genomic attributes affect drug responses in cancer is crucial for personalized oncology. Deep learning, an advanced computational method, has demonstrated significant potential in identifying and predicting these intricate interactions. One such example is the DeepDR model, which predicts how cancer cells respond to drugs. However, not all researchers have the computational resources and programming expertise to leverage this potential. Here, we introduce shinyDeepDR to bridge this gap by providing an intuitive and user-friendly web platform to access DeepDR. In the broader scope, we envision that tools like shinyDeepDR will advance cancer research by making sophisticated computational models more FAIR (findable, accessible, interoperable, and reusable).