Representation Learning Duck

I have found a principled way to recover known and find new drug targets using the t-cell perturbation data for any disease whilst highlighting the interpretability of how those drug targets affect the proceeding biological programs. I have borrowed methods from the field of causal representation learning to build relationships between the latent programs and found how perturbations would cascade down programs and how it effects each of them in a connected manner. This helped with the interpretability of the results of novel drug targets found for SLE and other potential diseases. Moreover, I have also built an agent that can be used to run the whole pipeline with any disease in mind, end to end, providing the results and potential novel drug targets.