WEB APP : Deep unsupervised learning methods for the identification and characterization of TCR specificity 🫁🧬
This dashboard aims to show how perform the different deep learning methods described in the paper Deep unsupervised learning methods for the identification and characterization of TCR specificity, when given a real CDR3 sequence or a personnalized one.
- Choose a model from which the representation will be computed.
- Type your own CDR3 sequence or click on the 'Generate' button to generate an existing CDR3 sequence at random.
- You can also choose random or personnalized v-gene and j-gene.
- It is also possible to compare all the models together on the same TCR in the Compare models tab.
- If you have any questions about this research, a chatbot is also ready to answer any questions that you may have in the ChatBot tab.
- The predicted embedding is computed and displayed.
- The predicted clustering is also displayed below the plot.
PLEASE NOTE: the website can sometimes be slow to load the text and the predictions. Please wait a few seconds for the content to load. This web application is hosted on Replit and Heroku.
🔗 Paper