A novel approach to chemical language modeling. First application of structured state space sequence models (S4) to *de novo* design.
A review of the deep learning approaches in low-data drug discovery. Future research directions are outlined.
We pharmacologically study chemical words and find that they can designate functional groups.
We present a python library to train more generalizable drug-target affinity prediction models.
A review of the deep learning approaches for structure-based drug discovery. Future research directions are outlined.
We present a novel training framework to improve the generalizability of drug-target affinity prediction models.